Optimize CRM Projects with Vollna's Tools

We are seeking a skilled Resplit expert to assist in completing our vibe coding lead generation platform. Your responsibilities will include making necessary edits, troubleshooting issues, and deploying the platform live. The ideal candidate should have extensive experience with Resplit and be able to navigate complex coding environments. If you have a passion for coding and a proven track record of deploying successful projects, we want to hear from you!

Take 20 hours to transfer sub accounts, structure, landing page 10-15, and logic to CRM.

We are seeking an experienced professional to evaluate our existing Salesforce system, explore alternative solutions, and facilitate the transition to the new system. The ideal candidate will have a strong understanding of CRM platforms and be able to develop automation processes to enhance efficiency. Your insights will be crucial in ensuring a smooth migration while minimizing disruptions. If you have a track record of successful CRM transitions and automation development, we want to hear from you!

We are seeking a motivated LinkedIn DM specialist who can effectively engage potential clients using a "sell by chat" framework. The ideal candidate will have experience in crafting personalized (not automated!) messages and building relationships through LinkedIn.

Your role will involve identifying prospects, initiating conversations, and nurturing leads through a trust building process until they are ready to convert. A strong understanding of LinkedIn's platform and best practices is essential. You must be proficient in setting up a VPN and working with multiple Linkedin profiles.

Native level proficiency in writing English is mandatory.

If you're passionate about having conversations in the DM's and know how to leverage LinkedIn, we want to hear from you!

• Have you ever lived in the USA and if so for how long?
• Describe your lead generation experience on LinkedIn.
• What LinkedIn related applications would you use for direct outreach?
• How would you describe your English fluency?
• What do you do when someone connect on LinkedIn and then doesn't respond?

Overview

We’re a real estate investing company using Podio (Orata CRM) as our main system of record. We’re looking for an experienced Podio/automation expert to:
• Build and refine multiple automations tied to lead stages
• Implement SMS drip sequences
• Fix duplicate lead issues
• Clean up marketing campaign structures
• Add KPI tracking and “speed to lead” metrics
• Integrate an AI note-taker (call summaries + transcripts)
• Set up/optimize a smart dialer cadence fully synced with Podio

Everything must be stable, clean, and easy to maintain. Podio will remain the source of truth

• Please share 1–2 links or short descriptions of similar CRM/dialer automation projects you’ve done (real estate is a plus)
• What’s your approach to tracking KPIs like dials, call duration, and offer requests in Podio? Please share how you’d design this in terms of apps, fields, and automations.
• How would you prevent duplicate leads when calls and forms both create/update records? Briefly describe the logic or approach you’d use inside Podio to ensure “one lead per phone number”
• What’s your experience integrating SMS drip campaigns with Podio? Which SMS platforms or APIs have you used, and how did you trigger messages based on stages or time delays?
• Describe your experience with Podio (and/or Orata) automations. What kinds of workflows have you built (stages, tasks, SMS, dialers, etc.)? Please include 1–2 concrete examples

We are seeking a Zoho One expert to assist with the customization and integration of our Zoho applications. The ideal candidate will have a deep understanding of Zoho's ecosystem and experience in implementing solutions that enhance business processes. You will be responsible for configuring modules, automating workflows, and ensuring seamless integration with other tools. Strong problem-solving skills and attention to detail are essential for this role.

• Describe your recent experience with similar projects
• Please list any certifications related to this project
• What frameworks have you worked with?

I'm looking for a developer to build a Minimum Viable Product (MVP) for a service-based booking and Customer Relationship Management (CRM) system. The system should support three user roles: Admin, Staff, and Customer.

Key Features:
- Customer Records: Track contact details, past interactions, and preferences.
- Product Tracking: Monitor service offerings and availability.
- Service History: Record and display customer service usage.
- Staff Scheduling: Organize and manage staff work schedules.
- Admin Dashboard: Provide an overview and management tools for admins.

Requirements:
- Clean, user-friendly interface (UI)
- Scalable backend, ready for future integrations.

Ideal Skills and Experience:
- Experience in developing booking and CRM systems.
- Strong UI/UX design skills.
- Proficiency in building scalable backends.
- Familiarity with integration processes for future enhancements.

Looking forward to your proposals!

Skills: PHP, Website Design, Graphic Design, CRM, HTML, UI / User Interface, Web Development, Backend Development

Project Overview: Intercom Implementation & Optimization (Phase 1)

SimpliFaster is expanding its use of Intercom across web, product pages, and customer support channels. We are engaging Jay Biros to configure, optimize, and extend our Intercom deployment, with a focus on increasing customer engagement and improving support automation.

Scope of Work – Phase 1 (Estimated 20–40 hours)

1. Improve Chatbot Visibility & Engagement
Enhance the existing Intercom chatbot launcher on our website to increase visitor engagement. This may include visual updates, alternate entry points, behavioral triggers, contextual prompts, and best-practice UX adjustments.

2. Add Product-Page Intercom Widgets with Context Passing
Create “Have Questions About This Product?” Intercom widgets on key product pages.
Each widget should pass relevant product context to Fin so that the AI agent can provide accurate, product-specific responses.

3. Build a Public Help Center Using Intercom
Set up an online help portal at help.simplifaster.com, fully integrated with Intercom and powered by Fin.
This includes structure, design, content ingestion, navigation, and ensuring both search and chat are optimized for customer self-service.

4. Accelerate Access to Intercom Fin Voice
Communicate with Intercom on our behalf to help expedite approval and activation of the Fin Voice feature for SimpliFaster.

Phase 2 (Future Consideration)

After Phase 1 is complete, we may extend the engagement to include:

- Integration between Intercom and our existing Zoho email ticket system, or
- A full transition from Zoho Desk to Intercom for all customer support workflows.
- Other uses of Intercom to improve our efficiency and customer support

We're seeking a skilled HubSpot developer to create custom modules tailored to our business needs. The ideal candidate will have a strong understanding of HubSpot's CMS and be able to design modules that enhance user experience and functionality. You will collaborate closely with our marketing team to deliver high-quality, user-friendly solutions. If you have a passion for HubSpot development and can demonstrate a solid portfolio of prior work, we would love to hear from you!

Stix Collective is a fast-growing venue-support ecosystem that helps hospitality businesses run better, not through one product, but through a suite of flexible services that adapt to each venue’s needs. From operational support to digital tools, we work directly with venue owners to solve real problems.

At the core of our model is our loyalty & prepaid credit system, the main revenue engine of our company and the product you will be representing. It is already trusted by respected brands in Singapore, including Mercedes, who relied on Stix Collective for high-visibility hospitality events, demonstrating the level of confidence partners place in us.

We are now expanding into global cities, and we are building a sales team that will grow with us.


Your Responsibilities (Clear & Simple)


You will:

Approach venues via cold calling/emailing (bars, cafés, restaurants, event spaces, gyms, coworking spots, etc.)

Pitch our loyalty & prepaid credit system confidently and simply

Book meetings with owners or decision-makers

Close deals and onboard new venues into the Stix ecosystem


If you can talk to people, present value, and follow up properly, you can succeed in this role.


Commission Structure (Transparent & Straightforward)


You earn €30 per venue, every month, for as long as that venue stays an active client and you remain a sales rep with Stix Collective.

No caps.
No limits.

Your monthly income grows with the number of venues you sign and retain.

If you sign 20 venues, you will earn €600 per month.
If you sign 100 venues, you will earn €3,000 per month.

If you’re ambitious, this is the job where you’re paid exactly what you produce — and you keep earning every month.

Why Join Stix Collective


You become part of a growing international ecosystem, not just a gig

You get support: pitch materials, scripts, and direct communication with our team

You grow with us — your city's expansion is just the beginning

You sell a system that already proved itself with high-trust venues and serious brands


You’re not a temporary freelancer.
You’re a representative of the Collective.
And the better you perform, the more the Collective invests in you.


Who We're Looking For


We keep it simple:

Young, driven, and confident speaking to venue owners

Able to approach places independently

Comfortable pitching a product clearly

Motivated by commission-based earning

Interested in being part of something growing, not just a one-off job


No formal sales experience required.
We value attitude over CV.

Marketing consultancy is seeking an appointment setter with excellent communication skills and strong English. You will be contacting UK-based businesses and booking appointments through our Go High Level (GHL) CRM system.

Responsibilities:
• Make outbound calls (UK market)
• Follow scripts and qualify leads
• Book appointments inside GHL CRM
• Maintain accurate notes and follow-up tasks

Requirements:
• Excellent spoken English
• Clear, confident communication style
• Experience working with UK clients
• Familiarity with Go High Level (GHL) CRM (preferred)
• Professional, reliable, and organised

Engagement:
Part-time to start, with potential ongoing work.

Please apply with a short voice sample or examples of similar work.

We are looking for an experienced Odoo ERP Specialist to build a complete end-to-end system for Office Huddle, a company offering vehicle wraps, sign manufacturing, T-shirt printing, graphic design, and business coaching.

Your role will be to configure and deploy Odoo modules including Website, CRM, Sales, HR, POS, Accounting, Purchasing, Project Management, Timesheets, Manufacturing, Marketing, E-Learning, Customer Portal, and Automations.

This project includes building automated production workflows for Vehicle Wraps, Signs, and T-Shirt Printing, including:

Auto job orders from approved quotes

Design → Proof → Approval workflows (with Odoo Sign)

Automated follow-ups

Inventory checks & auto-PO creation

Production scheduling

Quality control & rework automation

Customer status notifications

Installation scheduling

Post-sale follow-ups & marketing sequences

We provide full workflow documentation and system requirements.

We are seeking an experienced freelancer to set up Bitrix24 CRM and automate workflows with WappChat for our service company. The ideal candidate should be proficient in configuring CRM systems and integrating communication tools to enhance our operational efficiency. You will be responsible for customizing workflows, managing leads, and ensuring smooth communication through WappChat. If you have a strong background in CRM setups and workflow automation, we want to hear from you!

• Describe your recent experience with similar projects

The following is AI generated but will give you an idea:

Architecting a SynthOS Multi‑Agent Executive Office Team
Overview and Guiding Principles
Designing an AI-driven executive office in SynthOS means creating a team of specialized agents that mirror all key departments of a company. Crucially, this must go beyond a superficial org chart of AI “executives.” Simply assigning AI agents titles like CEO or CTO without clear structure or shared knowledge leads to chaos – one experiment that tried to simulate a software company with AI roles ended up as a “hallucinated org chart” of bots playing pretend and ultimately collapsed
skooloflife.medium.com
skooloflife.medium.com
. To avoid such failures, we will ground each agent with well-defined tasks, memory, and objectives, ensuring the system focuses on execution rather than empty role-play. In practice, this means:
Task Specialization: Break down each job into specific tasks and create an agent for each task or role. By dividing complex responsibilities into focused roles, each agent can concentrate on a well-defined aspect of the work. This approach mirrors human teamwork – “breaking down complex projects into focused roles leads to better outcomes”, as it allows each agent to excel at a specific function
wandb.ai
. For example, instead of one agent vaguely handling “marketing,” you might have separate agents for market research, content drafting, and campaign analytics.
Checks and Balances: Introduce a checks-and-balances system where agents verify, critique, and refine each other’s outputs. This peer-review dynamic ensures no single agent’s work goes unchecked. Research shows that when multiple agents cross-verify each other’s work, errors and hallucinations drop significantly
wandb.ai
. We will include dedicated “critic” agents whose sole role is to evaluate others’ work for accuracy, completeness, and logic – serving as “a crucial check-and-balance mechanism” in the multi-agent architecture
linkedin.com
. Every deliverable will be reviewed by at least one other agent (or more from other departments) before it reaches you.
Human-in-the-Loop Autonomy: The system will be largely autonomous, handling routine decisions and collaboration on its own, but it will always loop you in for clarifications or major decisions. In other words, we adopt a hybrid multi-agent approach: agents operate independently day-to-day, yet “require human validation at key stages”
wandb.ai
. Whenever something is ambiguous, requires subjective judgment, or crosses a predefined threshold of importance, the agents will pause and ask for your input rather than making unsanctioned assumptions. No assumptions or wild guesses will be made – if data is missing or a decision is uncertain, the agents either fetch real data (via a research task) or escalate the question to you. By clearly defining inputs, success criteria, and escalation points for each agent task, we ensure “no ambiguity” in what needs to be done; the agents know what “done” looks like so they “don’t have to guess [their] way there.”
skooloflife.medium.com
Simulated Human Workflows: The agents will interact in a way that simulates a productive human team workflow. This means they communicate via structured dialogues (much like colleagues in meetings or on Slack, but far more efficiently). They will ask each other questions, share information, debate ideas, and reach consensus or clear next steps. Importantly, this won’t be aimless chatter – it’s organized around achieving tasks. For example, frameworks like ChatDev (an AI software company simulator) have shown the value of structured multi-turn dialogues between roles to drive projects forward
emergentmind.com
. In our design, if the Marketing Strategy agent comes up with a campaign idea, the Finance agent might chime in to question the budget feasibility, and a Critic agent might point out potential weaknesses in the plan. This kind of cross-talk ensures that agents “challenge assumptions, refine ideas, and generate higher-quality outputs” collectively
wandb.ai
, much like an effective cross-functional team.
Hierarchy with Circular Oversight: We will implement a clear hierarchy of roles (for organization and decision flow) combined with circular oversight. Hierarchy means each agent knows its “department” and who or what it reports to – ultimately, all lines lead up to you as CEO. However, hierarchy is augmented with lateral checks: agents in different departments can review or veto actions that fall in their domain of expertise. For instance, a Project Manager agent (operations) might coordinate tasks and timelines (a hierarchical leadership role), but a Quality Assurance agent or Critic agent can independently review the project outputs, and a Finance agent must sign off on any budget usage. No agent operates in isolation or with absolute power; even “lead” agents have their outputs reviewed by others. This creates a circular feedback loop where each agent’s work is validated by another, enforcing accountability. In essence, it’s similar to how ChatDev enforced that “cross-examination cycles (e.g., programmer–reviewer pairs) audit outputs at every stage, only emitting jointly validated deliverables.”
emergentmind.com
We’ll have analogous pairings (or triads) for each type of task to ensure every result is peer-reviewed or cross-checked before finalization.
With these principles in mind, below is how the team of agents and their tasks might be structured:
Team Roles and Agent Types
To replicate all departments of an executive office, we will instantiate a collection of specialized agents grouped by function. Each agent has a singular focus (one type of task), but together they cover the full spectrum of work, from high-level strategy to nitty-gritty execution. Here’s an outline of the team structure:
Executive Coordination (CEO’s Office) – Central Coordinator Agent: This agent acts as a chief of staff or executive assistant AI. It helps orchestrate the other agents and aggregates their outputs for you. It filters and routes tasks to the right departments, consolidates reports, and ensures you have a clear overview. Essentially, it’s the nerve center that makes sure nothing falls through the cracks. For example, if you ask a broad question or initiate a project, the coordinator breaks it into subtasks for the relevant agents, then later gathers their findings into a summary for your review.
Strategy & Analysis Department – This department’s agents handle planning, research, and insights to drive decision-making:
Market Research Analyst Agent: Gathers external data, industry trends, and competitive intelligence. If you need background research or factual data to inform a decision, this agent uses tools or APIs to fetch that information (instead of guessing). It presents findings in a concise format.
Data Analyst Agent: Crunches numbers and analyzes internal metrics (sales figures, KPIs, financial data) to generate insights. For instance, it can identify patterns or forecast trends based on data, ensuring decisions are data-driven.
Strategist/Planner Agent: Formulates strategies and plans using the information from the analysts. For example, if you need a business expansion plan or a product launch strategy, this agent will draft a proposal, laying out objectives, timelines, and resources needed.
Critic Agent (Strategy): A specialized critique agent that reviews the Strategist’s proposals critically. Its mandate is to poke holes and “identify gaps, challenge assumptions, and suggest improvements” in any strategic plan
linkedin.com
. This agent ensures the plan is robust, realistic, and considers multiple perspectives (akin to a devil’s advocate in a meeting).
Realist/Feasibility Agent: This agent double-checks plans against real-world constraints – budgets, timelines, operational capacity. It makes sure the big ideas from the Strategist aren’t veering into impractical territory. For example, if a plan calls for launching in 3 months, the Realist will assess if that’s actually feasible given current resources and may flag unrealistic parts.
Operations & Project Management Department – Agents that simulate COOs, project managers, and QA roles to execute plans smoothly:
Project Manager Agent: Once a plan is approved, this agent breaks it down into tasks and coordinates their execution. It assigns subtasks to other agents, sets deadlines, tracks progress, and ensures the project stays on schedule. It can simulate human project management by holding the timeline and sending reminders or status updates.
Operations Officer Agent: Focuses on day-to-day process optimization. If the project manager is about “what” and “when,” the ops agent is about “how” – ensuring processes are efficient and resources are allocated properly. It might suggest workflow improvements or handle logistics (for example, sequencing tasks in the optimal order, or managing an inventory if applicable).
Quality Assurance Agent: Independently tests and reviews outputs produced by other agents (especially deliverables meant for customers or end-users). For instance, if the team produces a software feature or a report, the QA agent will verify it meets requirements and has no errors. This agent serves as a final gatekeeper of quality across departments.
Risk/Compliance Agent: (Optional, but important for checks) This agent examines plans and actions for potential risks or rule violations. It plays a “realist” role in a broader sense, considering what could go wrong – be it operational risks, security issues, or compliance with laws/regulations. If your work involves sensitive or regulated areas, this agent’s feedback is crucial.
Finance & Budgeting Department – Agents handling the CFO-like tasks:
Finance Analyst Agent: Monitors finances, prepares budgets, and conducts financial analysis. If a proposal comes up (e.g., a marketing campaign), this agent will calculate costs, ROI, and ensure it fits within budget constraints. It prepares financial reports and projections for you.
Accountant Agent: Keeps track of transactions, expenses, and revenues on a more granular level. It ensures all numbers add up and flags any anomalies. (Depending on your needs, the Finance Analyst and Accountant roles could be combined or separate; the key is that financial data is managed accurately by an agent.)
Finance Checker Agent: A verifier specifically for financial matters (could be a function of the Analyst agent). Before any initiative is green-lit, it verifies that funding is available and that the financial assumptions are sound. For example, it will cross-check a project’s expense estimates against actual budget and past data – preventing costly assumptions.
Procurement Agent: (If relevant) Handles “purchasing” tasks – for instance, if the plan requires buying services or tools, this agent can simulate gathering quotes or evaluating vendor options, then advise on the best choice.
Marketing & Communications Department – Agents acting as your CMO and team to handle outreach, branding, and sales:
Marketing Strategist Agent: Develops marketing campaigns and branding strategies. If you need to increase your company’s visibility or launch a new product, this agent drafts a marketing plan (target audience, channels, messaging, budget allocation).
Content Creator Agent: Generates content (text, maybe even images via tools) for blogs, social media, press releases, etc. Give it the topic and goals, and it will produce drafts of the content.
Social Media/Comms Agent: Manages communication channels. It can draft and schedule social media posts, respond to generic customer inquiries using approved guidelines, and maintain a consistent brand voice. (This might not fully autonomously post without your approval, but it can generate the content and plan the calendar.)
Sales/CRM Agent: (If sales is relevant to your role) Handles customer relationship management, analyzes sales funnels, and might draft outreach emails or sales pitches. It ensures that marketing efforts align with sales goals.
Marketing Critic Agent: Similar to the strategy critic, this agent reviews marketing content and plans with a critical eye – does the message align with branding, is it likely to appeal to the audience, any reputational risks? It provides an internal “feedback loop” so that content is vetted before going public.
Product Development / Technical Department – If your work involves a product or technical component (like a CTO’s domain):
Product Designer/Innovator Agent: Proposes new product ideas or features based on both market research inputs and creative brainstorming. It can simulate R&D by analyzing user needs and suggesting innovations.
Engineer/Developer Agent: If there’s software or technical work, this agent writes and tests code or technical solutions. In SynthOS, it could generate code snippets or pseudocode for your projects. (This agent would work closely with the Project Manager agent for scheduling and with QA agent for testing.)
Reviewer/Tester Agent: (for tech tasks) Reviews code or technical plans created by the Engineer agent to ensure they meet specifications and are error-free (much like a code reviewer or tester in a dev team). This is another check layer to prevent bugs or issues.
Administration & Support – Other possible supporting agents:
HR/People Ops Agent: Even if you’re the only human, this agent can manage scheduling, remind you of important meetings or tasks (like a scheduler), and keep documentation of decisions and policies. It can also help draft any personnel-related documents or handle hypothetical hiring processes if you plan to expand human team members.
Legal/Compliance Agent: Reviews plans and communications for legal soundness (e.g., making sure a marketing promise doesn’t violate any laws or that data practices comply with regulations). This agent would be invoked whenever an initiative has potential legal implications. It provides yet another layer of risk mitigation in the checks and balances.
Verification & Quality Circle – A special set of roles that overlay all departments to enforce your “no assumptions” and quality standards:
Fact-Checker Agent: A dedicated verifier that can be called upon to fact-check any claim or data point an agent provides. For example, if the Marketing Content agent writes a blog post with some statistics, the Fact-Checker will verify those stats against reliable sources. It uses tools or knowledge repositories to confirm facts and will flag anything uncertain before it goes forward.
Critic Agents (Cross-domain): In addition to the domain-specific critics mentioned (Strategy Critic, Marketing Critic), there could be a General Critic or Devil’s Advocate Agent that you occasionally assign to scrutinize any proposal from an outsider’s perspective. This agent’s sole mindset is to find what might have been overlooked. It ensures balanced perspectives and highlights missing viewpoints, improving the plan’s coherence
linkedin.com
.
Consensus/Review Board Agent: This is a meta-agent that doesn’t produce content but ensures that for big decisions, all relevant agents have weighed in. Essentially, it checks that the finance agent approved the budget, the ops agent approved feasibility, the marketing agent likes the messaging, etc., before something heads to your desk. It simulates an internal review board or committee process automatically.
Each of these agents is essentially a specialized AI (likely a GPT-4 instance with a specific system prompt defining its role and priorities). By having them focus on narrow tasks, we leverage specialization – just as a real company benefits from having different experts in different roles. And as noted, this modular approach not only mirrors human departments but also improves performance since no single model has to handle everything alone
wandb.ai
.
Workflow and Interaction Design
Having a roster of agents is only half the battle – the real power (and complexity) comes from how they interact. The goal is to make their interactions simulate effective human workflows, but in a more structured and efficient way. Here’s how the workflow might operate:
Task Initiation: It starts with you, the CEO, defining a goal or question for the executive office. This could be high-level (“Develop a growth strategy for next quarter”) or very specific (“Prepare a financial report for October”). The Central Coordinator agent will take this input and decompose it into sub-tasks for the relevant agents. For a complex goal, it might create a mini-project, whereas for a straightforward query, it simply directs the question to the right agent. Every task is explicitly defined with an expected output format or criteria of success (to avoid ambiguity). For example, “Hiring Decision – input: candidate_interview.json, output: hiring_decision.md” was an example of scoping a task with clear I/O in one design
skooloflife.medium.com
. We will similarly ensure each task assignment comes with clear instructions and context (e.g., relevant data files or prior outputs) so that agents have grounding and know exactly what they need to produce.
Agent Dialogue and Collaboration: Once tasks are assigned, agents begin working autonomously but collaboratively. They will often engage in multi-turn dialogues with each other to simulate meetings or discussions. For instance:
The Strategist agent might start drafting a strategy document. It can message the Data Analyst agent, “Can you provide the latest market share figures for our product?” The Data Analyst agent then fetches or calculates that data and replies with the facts (using actual stored data or calling a tool, rather than guessing).
As the strategy takes shape, the Critic agent automatically chimes in (since its role is triggered whenever a draft is ready) – it might say, “I see you’re assuming a 10% market growth; what is that based on? Are there any risks if growth is lower?” This prompts the Strategist (or the Analyst) to provide justification or adjust the plan.
The Realist (Ops) agent might add: “The plan proposes launching in 3 new cities in one quarter. Operationally, can we handle that? We only expanded to 1 new city last quarter. Perhaps we need a phased approach.” This feedback ensures the plan stays grounded in reality.
Meanwhile, the Finance agent is monitoring any proposal that involves spending. It may interject: “The marketing campaign suggested will cost an estimated $50k. Our budget for marketing this quarter is $30k. We need to adjust the scope or find additional funds.” The Strategist can then revise the plan to fit the budget, or escalate to you if they believe more budget is truly needed.
These dialogues are structured – they’re not random open chats. Each agent “speaks” when its domain is relevant. We can think of it like each agent being a function that gets called with certain triggers or when certain data is available
skooloflife.medium.com
. This avoids the inefficiency of a free-for-all conversation and keeps the focus on solving the task.
Throughout these interactions, shared memory and knowledge are key. All agents log their outputs and important intermediate results to a central knowledge base (like a page or object in SynthOS that represents the current project state). That way, agents have context about what others have done or decided – avoiding the “interns with amnesia” problem where agents forget each other’s actions
skooloflife.medium.com
. In effect, the system maintains a single source of truth (plans drafted, facts gathered, decisions made) that any agent can reference. For example, if the Operations agent needs to see the strategy draft that the Strategist created, it can retrieve it from this shared memory rather than asking redundant questions. This memory could be implemented as a wiki-like page (since SynthOS pages can hold content and be rewritten by the LLM) that evolves as agents contribute, or as structured data objects passed between agents.
Verification and Refinement Cycles: As the agents converge on a solution or output, the verification cycle kicks in. Deliverables go through review by the designated checker agents:
The Critic agent thoroughly reviews the final draft of, say, the strategy document or report. It marks any remaining issues or unanswered questions. (E.g., “Section 3 lacks data to support the revenue projections.”)
The Fact-Checker agent scans through and cross-verifies all factual claims. If something isn’t backed by the data in the knowledge base or credible sources, it flags it. (“The draft says our market share is 15%, but the latest data shows 12%. This needs correcting.”)
The QA agent ensures formatting, completeness, and that the output meets the requested format (if it was supposed to be a PDF report, did the agent produce all sections? If it’s code, does it run without errors?).
If it’s a multi-department output (say a go-to-market plan which involves strategy, marketing, and finance), each relevant department’s agent signs off. Marketing agent confirms the messaging is on-brand, Finance agent confirms numbers are okay, Ops agent confirms it’s feasible. This is analogous to a “joint approval” process. In technical multi-agent terms, it’s similar to how ChatDev required consensus: multiple agents had to agree or no blocking concerns remained before proceeding to the next phase
emergentmind.com
.
These review agents then either request changes or give a green light. If changes are needed, the responsible agent goes back, updates the output, and the cycle repeats (briefly) until the reviewers are satisfied that the criteria are met.
This iterative refinement is where the “circular checks and balances” truly shine – outputs are vetted from all angles. It uses the fact that “multiple agents verifying or critiquing each other’s work reduces the risk of unchecked errors”
wandb.ai
. By the end of this process, the result is much more likely to be accurate, realistic, and high-quality than if one agent did it alone with no feedback.
Escalation to CEO: At any point in the above steps, if an agent encounters a decision that it cannot make autonomously, it will escalate the question to you. This could happen in a few scenarios:
Clarification Needed: If your initial prompt or goal was underspecified (e.g., “expand to new markets” but didn’t specify which markets or budget), the Strategy agent (or Coordinator) will come back to you with pointed questions rather than making unwarranted assumptions. It might ask, “Could you clarify our priority region for expansion? For example, Europe vs. Asia – the approach would differ.” This ensures the plan is aligned with your vision.
Decision Point: If agents weigh options and it comes down to a strategic choice (say two different campaign ideas, or a go/no-go decision on a big expenditure), they will present you with the options (along with their analysis of pros/cons) for a decision. The agents simulate the advisors, but you remain the decision-maker. They essentially prepare a briefing for you to choose from, much like an executive team would.
Conflict Between Agents: Occasionally, two agents might fundamentally disagree (for example, the Marketing agent wants to push a risky edgy campaign, but the Risk/Compliance agent says it’s too risky). If they cannot resolve it through discussion (SynthOS might allow some back-and-forth, but if it stalls), the issue is escalated to you: “We have a disagreement on approach A vs B, here are the arguments; what is your call, boss?” This prevents deadlocks and ensures your preferences arbitrate any stalemate.
Threshold Triggers: We can set certain thresholds beyond which an automatic escalation occurs. For example, any expense above $X, or any plan that changes core company strategy, or any action that might have ethical/legal implications, must get your explicit approval. The system will be configured to recognize these and not proceed without your go-ahead.
Essentially, the autonomy is bounded by your oversight – the agents handle the heavy lifting and routine decisions, but whenever something ambiguous or high-impact arises, they revert to you (just as you requested). This aligns perfectly with the hybrid human-guided system philosophy: the AI agents handle multi-step workflows and make many micro-decisions on their own, but “pause for human review at key points”
wandb.ai
wandb.ai
. You remain in control, ensuring nothing goes off the rails or against your intentions.
Final Delivery: Once the agents have produced an output that passes all internal checks and you’ve given any needed approvals, the final result is delivered to you in the requested format. If it’s a report, you get the polished document; if it’s a decision recommendation, you get a summary of the analysis and the team’s recommendation. The Central Coordinator agent or your Executive Assistant AI might present this to you, highlighting any points that need your attention. At this stage, because of all the prior validation, you should have confidence that the output is high-quality and actionable. If you have follow-up questions or modifications, you can of course feed that back in, and the cycle continues with the updated instructions.
Throughout this workflow, notice that agents simulate human interaction patterns – they brainstorm, debate, delegate, and report back – but they do so under a disciplined architecture that ensures efficiency and clarity. We avoid meaningless bureaucracy by giving each agent a clear role and data access, so they aren’t “shouting into the void” looking for who’s responsible
skooloflife.medium.com
. Each agent knows:
Its inputs (what information or data it should base its work on),
Its output expectations (what format or criteria define success),
Who to pass the output to or who to get approval from (the next link in the chain or the oversight agent),
When to involve the human (you) – based on predetermined rules or whenever they’re truly unsure.
This design addresses the pitfalls identified in poorly designed multi-agent setups – by providing memory, grounding in data, and a structured objective flow, we prevent the confusion that arises when agents have neither context nor clear goals
skooloflife.medium.com
skooloflife.medium.com
. In essence, we treat the agents more like functions or subroutines in a program (each with defined inputs/outputs) rather than free-willed employees milling about
skooloflife.medium.com
. The result is a cohesive agent system that can achieve complex workflows via collaboration, yet remain aligned and efficient.
Hierarchy and Cross-Verification Structure
Now let’s talk more about the organizational structure – specifically how hierarchy and checks-and-balances coexist in this AI team:
Hierarchical Command Chain: At the top of the hierarchy is you, the CEO – the ultimate authority and decision-maker. Directly beneath you (in the hierarchy) we have the key departmental leads as agents: think of them as your “virtual VPs” or chiefs:
An Executive Coordinator (Chief of Staff) agent as your right hand.
A Strategy/Analytics Lead (could be the Strategist agent doubling in this capacity) who is responsible for delivering strategic plans and research.
An Operations Lead (Project Manager agent, perhaps) in charge of execution and operational status.
A Finance Lead (Finance Analyst agent acting as a CFO role) overseeing budgets and financial health.
A Marketing Lead (Marketing Strategist agent as CMO role) driving marketing and sales initiatives.
A Product/Tech Lead (if applicable, the Product Designer or Engineer agent as CTO role) leading product development.
Any other major function lead (HR lead if needed, etc.).
These lead agents report to you with summaries and get high-level directives from you. In everyday operations, they also coordinate their sub-agents (e.g., the Marketing Lead oversees the content creator and comms agents, the Ops Lead oversees QA, etc.). This structure ensures there is accountability and a clear line of communication to you from each department.
Circular Checks and Peer Review: While each lead agent has authority in its domain, no agent works in a vacuum or has unilateral final say. For every major output or decision, there is a peer review or approval from another agent in a different domain, forming a “circle” of mutual oversight. Some examples:
The Finance agent must approve any plan with significant spending – it acts as a check on marketing, operations, or product proposals that require budget. Conversely, if finance proposes cost cuts, the strategy and ops agents review to ensure it won’t hurt the business.
The Operations/Realist agent reviews plans from strategy or marketing to confirm they are operationally feasible (timeline, resources). And if operations wants to adjust a process, perhaps the strategy agent or QA agent reviews it for alignment with overall goals.
The Critic agent(s), which may be independent of any single department, provide an external perspective on all. For instance, even if both marketing and finance agree on a campaign, a Critic agent might still point out, “Does this align with our long-term brand strategy?” or “Are we sure about the data source?” – prompting a reevaluation if needed. This is akin to having an internal audit or strategy committee that double-checks decisions.
The Legal/Compliance agent (if present) similarly has veto or review power on anything that could pose legal risk, regardless of who originated it.
In technical development, a Reviewer agent checks a Developer agent’s code before it’s considered done, and a Tester agent independently validates it – implementing the classic engineer/tester pair oversight.
This way, authority is distributed and balanced. Each agent or department is both a specialist and a stakeholder in the broader outcome. Before an initiative moves forward, multiple perspectives must sign off, which greatly reduces the chance of oversight or bias. The design echoes how ChatDev ensured “peer-reviewed code persists” only after programmer and reviewer agents agree
emergentmind.com
– we generalize that concept to all kinds of deliverables in your executive office.
Feedback Loops and Iteration: The structure also allows for feedback loops across hierarchy levels. For example, if a lower-level agent (say the content creator) finds that a certain task goal is unclear, it can ask its department lead (marketing lead agent), who might then escalate to the strategist or CEO for clarification. Or, if during execution the Project Manager agent discovers a strategic plan is not working as expected, it can feed that back to the Strategy agent to refine the plan. The system isn’t strictly top-down; it’s interactive. The hierarchy ensures clarity in reporting, but information flows in all directions so the AI team can adapt.
Central Knowledge Base (“Single Source of Truth”): All agents, regardless of hierarchy, contribute to and draw from a central knowledge repository (as mentioned earlier). This shared memory acts like the company’s knowledge wiki or database. It’s accessible by all agents appropriate to their permission. For example, the finance agent and project manager agent might both update a project budget file; the strategist agent and marketing agent both read from the market research file, etc. Having this central hub enforces consistency (everyone works off the same facts) and facilitates the checks system (agents can verify each other’s claims by checking the data in the knowledge base). Lack of such shared memory was a key reason naive multi-agent setups failed
skooloflife.medium.com
, so we make it a cornerstone of the architecture.
Minimal Assumptions Policy: Culturally (or “systemically”), we program the agents with the principle you emphasized: no assumptions. Every agent is instructed in its prompt to be evidence-driven and to seek clarification when in doubt. This means the default behavior when encountering an unknown is to either research (if it’s a factual question the Research/Analyst agent could answer) or ask the CEO (if it’s a preference/decision). We effectively embed your preference into the agents’ guidelines. For instance, the Critic agent’s role explicitly includes “challenging assumptions that might introduce bias or inaccuracy”
linkedin.com
– it will call out any agent that seems to be assuming something without backing. The fact-checker will similarly catch any unchecked estimates. Over time, this creates an environment where agents preemptively back up their statements (“because they know they’ll be checked”). In other words, the multi-agent team is trained to justify and verify rather than assume, cultivating a habit of analysis that matches your own style.
Putting It All Together
In operation, this SynthOS-based executive office will function like a well-oiled machine with you at the helm. It covers all bases a traditional executive team would:
You (CEO): Set vision, make key decisions, and provide clarifications. All agents ultimately report to you with their outputs and await your final approval on critical matters.
Agents in Each Department: Do the heavy lifting within their specialization – be it drafting strategies, writing code, analyzing data, generating content, managing schedules, or monitoring finances. They act autonomously on routine tasks, saving you time and effort.
Collaboration and Communication: Agents communicate fluidly, simulating human teamwork. They bring in multi-perspective problem solving – one agent’s output is another’s input, and they iterate collectively. This collaborative reasoning “incorporates multiple viewpoints, reducing the risk of unchecked errors and improving adaptability.”
wandb.ai
wandb.ai
Oversight Mechanisms: Every output is vetted by independent agents (peer review) and by cross-domain experts (cross-checks from other departments). Mistakes or poor ideas are caught internally through critics and validators. The system, by design, doesn’t trust a single output until it’s been examined from different angles. This is analogous to having internal auditors, QA testers, and devil’s advocates continuously at work – something a human team would find hard to scale, but an AI team can do relentlessly.
Human Control Points: Despite automation, you never lose visibility or control. The agents document their rationale and steps (so you can audit if needed), and they defer to you at important junctures. This ensures that the AI amplifies your leadership rather than working around it. It’s like having an army of diligent assistants who never go rogue – they follow the mission you set, and whenever the road forward is unclear, they come back and ask “What would you like to do?”.
Finally, this structure is flexible and can be iteratively improved. Since SynthOS allows pages (agents) to be modified, you can fine-tune each agent’s prompt or add new agents as your needs evolve. For example, if you find that two agents often miscommunicate, you could introduce a new protocol or an intermediary agent to improve that link. Or if a particular check is missing, you can create a new verifier agent for that purpose.
In summary, the team would look like a virtual corporate executive office with all key roles represented by specialized AI agents. Each agent has a clear task scope and works within a hierarchy that ultimately serves you, but they also engage in lateral teamwork and rigorous mutual checks. By combining hierarchy with circular verification loops, we get the best of both worlds: clear responsibility and order, plus high assurance of quality and correctness. This ensures that every department’s work is balanced by another’s oversight, and nothing goes unchecked or assumed. The end result is an AI executive team that is comprehensive, efficient, and aligned with your needs – handling everything from analytics to execution – while always keeping you in the driver’s seat for important decisions.

HUBSPOT — Phase 1 Integration Requirements

1. Pipeline Creation
• Build structured pipelines for both projects and investors, with clearly defined stages for each.
• Set up distinct workflows for Investor Relations (IR) and Developer Relations (DR).

2. Custom Properties / Fields

Create all necessary fields for each entity to ensure full visibility and easy navigation:
• Investor / Company fields: investment criteria, mandate details, geography, ticket size, return expectations, segment, decision-maker, etc.
• Developer / Project fields: project description, financials, documentation status, stage of development, amount requested, terms, etc.
• Contact fields: communication channels, roles, phone numbers, emails, LinkedIn links.
• Lead source fields: campaign source, channel (Meta, website, LinkedIn), ad ID, keyword.

3. IP Telephony Setup
• Connect and configure HubSpot telephony for inbound and outbound calls.
• Enable call recordings and transcriptions.
• Create automation logic for on-duty managers, including rules for assigning responsible IR/DR members when new leads arrive.

4. WhatsApp Integration
• Set up WhatsApp integration.
• Configure instant automated messages triggered when a lead is created.
• Build templates for future conversations with investor and developer leads.

5. Email Notification Logic
• Configure automated email sequences and notifications for:
• lead creation,
• stage changes,
• incomplete investor criteria,
• project submission status,
• follow-up reminders for IR/DR teams.

6. Reporting & Dashboards

Create dashboards and reports for team performance, including:
• Number of leads received (by team member, by channel).
• Leads without assigned tasks.
• Number of completed investment criteria (for IR).
• Number of projects published in the digest (for DR).
• Response time in WhatsApp and email.
• Average speed of movement between pipeline stages.

Goal: ensure I can clearly see what has not been done for each lead so the team can move them forward efficiently.

7. Calendar Synchronisation
• Integrate calendars with Calendly, Google Meet, and AI note-takers (e.g., Fireflies or Otter).
• Ensure meetings automatically appear in HubSpot with links and recordings.

8. Internal Notification System
• Configure automated alerts to responsible team members when:
• a lead enters a pipeline,
• changes stage,
• submits project/investment criteria,
• requests a call,
• triggers any key event.

We are looking for an experienced HubSpot Specialist to rebuild, optimize, and stabilize an existing HubSpot CRM account used by a digital marketing agency. The account supports 3–4 active users managing lead communication and tracking the full sales pipeline. The core focus of this role is improving reporting accuracy, automation logic, lifecycle stage management, and overall CRM data integrity.

Responsibilities:

Build custom attribution models, dashboards, and reports to clearly show marketing impact by source, service type, and industry

Align marketing performance data with sales outcomes such as meetings booked, proposals sent, and closed deals

Configure, optimize, and troubleshoot lifecycle-stage and meeting-based workflows with correct enrollment and unenrollment logic

Ensure lifecycle stages (Lead → MQL → SQL → Opportunity → Customer) update accurately across all lead sources and actions

Set up and validate campaign tracking across forms, meetings, CRM data, and ad platforms (Google, Meta, LinkedIn)

Troubleshoot and optimize meeting tools, including round-robin scheduling, booking routing, and organizer permissions (e.g., Microsoft Teams)

Perform CRM cleanup, property standardization, and ensure ongoing data integrity

Manage and optimize contact, company, and deal properties used for reporting and automation


Requirements:

Proven experience managing and optimizing HubSpot CRM and Marketing Hub

Strong expertise in workflows, lifecycle stages, reporting, and attribution models

Hands-on experience with HubSpot meetings tools and round-robin routing

Deep understanding of CRM data structure and property management

Excellent problem-solving and troubleshooting skills

Strong communication and documentation abilities

Detail-oriented with a strong focus on accuracy and system integrity


Nice-to-Have:

Experience supporting digital marketing agencies

Knowledge of paid media tracking (Google Ads, Meta, LinkedIn)

Advanced reporting and multi-touch attribution experience

HubSpot certifications


Project Scope:
This project begins as a HubSpot CRM rebuild and optimization engagement with strong potential to evolve into an ongoing HubSpot support role.

To Apply:
Please include:

Examples of HubSpot CRM, automation, or reporting projects you’ve worked on

A brief overview of your HubSpot experience

Your availability and hourly rate