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Two data sources are starting to paint a picture of Maia's early impact on entrepreneurs.<h3>ILO Colombia Study: Behavior Change in Coffee Country</h3>The International Labour Organization conducted an independent pre-post survey of coffee farmers in Colombia's Huila region—a baseline and follow-up two months later. The results were:Business practices: &nbsp; - Farmers keeping financial records: 56% → 78% &nbsp; - Formalized businesses: 2% → 17% &nbsp; - 55% of users reported directly implementing changes based on MAIA interactionsAgricultural practices: &nbsp; - Harvesting only mature beans: 80% → 85% &nbsp; - Minimizing waste/residues: 72% → 87% &nbsp; - Proper fertilizer application: 88% → 91% &nbsp; - Using climate-appropriate seeds: 83% → 87%The formalization jump—from 2% to 17%—is particularly notable. Formalization is notoriously hard to move. One farmer shared: "MAIA helped me formalize my coffee brand and create the company with all the legal requirements."What users valued most was having expert guidance available on demand. As one producer put it: "It's like having the agronomist right there on your phone." Another noted: "I used to mix fertilizers and composts together. Now I learned there are products that shouldn't be combined—MAIA explained that to me."<h3>Peru User Surveys: Self-Reported ROI</h3>Separately, we recently began surveying MAIA users in Peru and Panama at months 2 and 3 about changes in their business finances. The questions are simple: have your costs gone down due to Maia? Have your sales gone up due to Maia? Users choose between no change, up to S/150/month (~10% of average MSME profits), or more than S/150/month.From the first 165 responses: Cost Reduction (Month 2): 44% reported lower costs, Sales Increase (Month 3): 58% reported higher sales.&nbsp;These numbers are a floor. At months 2-3, MAIA's coaching relationship is just beginning. User profiles are still taking shape, and most haven't completed full coaching cycles. The progression from 44% (month 2) to 58% (month 3) illustrates momentum building over time. But still just using these early results, the average user reports S/47/month in cost savings and S/60/month in sales gains (at the bin midpoints). At a ballpark program cost of $1/user/month, that's a 12-17x ROI.According to <a data-mce-href="https://voxdev.org/voxdevlit/training-entrepreneurs" href="https://voxdev.org/voxdevlit/training-entrepreneurs" target="_blank" rel="noopener">https://voxdev.org/voxdevlit/training-entrepreneurs</a>, standard entrepreneurship training programs (typically 5-7 days in a classroom at ~$177/participant) produce around 5% sales gains and 10% profit improvement. The most effective "personal initiative" programs cost ~$750/participant and achieve 30% profit gains over two years. MAIA is showing comparable behavior change at a fraction of the cost: $12/year versus $177-750 for traditional training—and delivered continuously rather than as a one-time event, meaning its impact should rise over time while the impact of one-time training fades.<h3>What We're Learning</h3>The ILO study surfaced an important insight: "MAIA facilitates progressive adoption of digital technologies in rural areas, especially when combined with technical support and contextualized content." Users valued personalized, locally-relevant guidance. This is what enabled adoption of an advanced AI tool by users with very low tech comfort.These are early numbers. The surveys are self-reported, sample sizes are modest, and respondents still in the first months of the coaching relationship. But the direction is clear: users are changing behavior, and they're attributing it to MAIA.We'll keep measuring and sharing what we learn.

Impact Numbers

Context is a bit of a buzzword in the AI space, but it is central to making tools like MAIA useful. Context is the difference between the general answer to a general question any entrepreneur can get out of ChatGPT, and a targeted next step to solve the entrepreneur's next most pressing problem, along with accompanying assets to make it easy to implement.&nbsp;One approach is for tools like Maia is to be integrated with, and even come from, an MSMEs large supplier or customer. So for example a small retailer may buy many of their products from a large distributor. If that distributor creates an AI advisor plugged into all of the shop's historical orders, it could immediately give targeted advice on day 1 with all this rich context. There are many tools being developed along these lines today. But beyond the technical challenges in building them, there are two fundamental problems that keep coming up.First is the organization's desire to put their fingers on the scales and direct responses towards their own ends. This can start innocently enough- let's make sure the tool has our entire price list and features loaded so it can give accurate information, but we won't spend time doing that for other distributors, that's not our job. And it progresses from there. It makes sense: why would a distributor spend money building a tool that suggests' its competitors products and services over their own? Or that encourages small suppliers to only sell to them instead of diversifing their distribution. In the end that just means the tool is not a real coach, it is not operating in the best interests of the entrepreneur.Second, the entrepreneurs themselves behave strategically. If that retail shop is having some financial problems, would they really seek help from their AI coach about it? Couldn't the supplier use that early information to proactively limit trade credit?So the rich context comes at the cost of some very messy unaligned incentives which undermine how useful the tool is for the entrepreneur, and if/how they use it.The other approach is to build that context over time, which is how Maia works. This takes longer and isn't as elegant as the other short cuts, but has the benefits of being completely aligned with our users. We've found that business profiles become quite useful for giving grounded advice for a user after only a few weeks, and we spend a lot of time finding high-value low-effort first uses of the tool, to give the business owners a quick win while building context (eg making logos, a user favorite).&nbsp;

Context is King

MAIA started in Peru, which remains our largest country, but one year ago we started working in Panama, in partnership with <a data-mce-href="https://ampyme.gob.pa/" href="https://ampyme.gob.pa/" target="_blank" rel="noopener">AMYPME </a>and the ILO. As in all countries where we operate, the first stage is a detailed proecss of adaptation with local experts. In the case of Panama, our initial focus was small-scale producers of coffee and vegetables, and the tool was adapted and validated with sector experts. With them we collected a series of key country-specific manuals, guides, and rules, ending with country-sector specialized prompts and knowledge bases for RAG. MAIA @AMPYME was born.After multiple rounds of testing, in the face of very positive user feedback the tool was made generally available. <a data-mce-href="https://www.instagram.com/reel/DP4L1NeDlZ3/" href="https://www.instagram.com/reel/DP4L1NeDlZ3/" target="_blank" rel="noopener">Here you can see Jackeline Munoz, Panama's minister of labor and workforce development, along with leadership from AMPYME and the ILO at their official launch of Maia</a> <figure id="figure-of710qks13mi7olx5l"><img id="of710qks13mi7olx5l" src="https://cdn.durable.co/blocks/3aPOnZBjZgu8MNUusiZVgKUcnXeuzusOp8wZP8ZkxLJqrhz4He5GYJDOuatGTpFU.jpg" alt="" title="" class="object-cover bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/3aPOnZBjZgu8MNUusiZVgKUcnXeuzusOp8wZP8ZkxLJqrhz4He5GYJDOuatGTpFU.jpg" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure> Panama has quickly grown to become MAIA's second largest country with thousands of users, and we are entring new rounds of validation and expansion with the ILO and AMPYME!

MAIA @AMPYME Panama

Here is the latest MAIA overview, all data as of mid-oct<figure id="figure-5b2bfb0ylmhdn7qol" class=""><img id="5b2bfb0ylmhdn7qol" src="https://cdn.durable.co/blocks/3achi9WTMClfHY6KtCzRmPi0XvHixpDeVKKD1GDEDrwNWQnjRLdWpMFTNvif61xi.png" alt="" title="" class="object-cover bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9; object-position: center center;" data-corners="default" data-aspect="16:9" data-caption="" data-positionx="undefined" data-positiony="undefined" data-fullwidth="false" data-mce-src="https://cdn.durable.co/blocks/3achi9WTMClfHY6KtCzRmPi0XvHixpDeVKKD1GDEDrwNWQnjRLdWpMFTNvif61xi.png" data-mce-style="aspect-ratio: 16/9; object-position: center center;"></figure><figure id="figure-6prnpn70njmhdn9ylr" class=""><img id="6prnpn70njmhdn9ylr" src="https://cdn.durable.co/blocks/20AcUW0ag6AIPXvXY8nPE7tMnnFKsGApYsEK9zY2P3cG6nPMqyIZuTfYlN7sexIp.png" alt="" title="" class="object-cover bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9; 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Maia Overview Presentation

<a data-mce-href="https://mypeasesoria.org/blog/maia-s--intellectual--architecture--situated-entrepreneurial-coaching" href="https://mypeasesoria.org/blog/maia-s--intellectual--architecture--situated-entrepreneurial-coaching" target="_blank" rel="noopener">The previous post</a> described Maia's appraoch to situated entrepreneurial coaching through a continuous coaching cycle, as well as its basis in the literature. How do we actually implement that in practice?About 90%+ of the time, the cue is Maia's tip of the week*. This used to be human-curated and fixed by sector, but now our coaching engine derives a customized tip for each user, the next idea/best practice with the highest marginal impact on their business. This is derived based on the user's own priorities and history as reflected in their entrepreneurial profile**, Maia's 8-dimension diagnostic of their business***, the country-sector specific knowledge bases we've built with local experts, and also considers emerging and seasonal themes via search. These tips are expressed via a set of WhatsApp template shells with a few different approaches.Interaction with the tool following the cue quickly takes the user towards the action plan, which is calibrated to the businesses' level of development and priorities, both as expressed in the conversation and in the profile. Along with the plan, Maia provides every asset it can to make taking the next step as easy as possible, such as templates, images, checklists, if-then scenarios, etc.The guided reflection and reward stage is implemented through a second weekly message. Unlike the cue, which brings in new information and ideas, this follow-up message looks backwards, encouraging and rewarding action and reflecting on results to overcome obstacles and find new opportunities. Again, implemented though a series of WhatsApp template shells.Interaction with the tool on this follow-up message leads directly to adjusting plans and taking corrective action when things worked poorly, and building habbits when things worked well. It naturally leads to a new cue, to start the cycle again.* The other 10% are inbound user questions. Current cadence is fixed weekly, our roadmap is to move to adapting the cadence to user preferences** A structured profile of each user, including key business characteristics and goals. Will be discussed in a future post.*** This is synthesized based on diagnostic tools and training programs from a variety of organizations like the ILO, the IFC, the FAO, and consulting companies. Will also discuss in a future post.

Part 2: Implementing this Architecture - MAIA's Coaching Engine

The Opportunity: Closing the "Adoption Gap"Traditional entrepreneurial training faces a well-documented "Adoption Gap." After multi-day courses teaching 20-30 new business practices, entrepreneurs typically implement only one or two. This leads to modest average profit gains of ~12.1% and leaves significant potential untapped. Maia is designed to close this gap, moving beyond one-time knowledge transfer to build lasting, high-impact habits through a continuous, AI-powered coaching cycle. The Continuous Coaching Cycle The architecture is a virtuous loop that turns insight into action and action into habit. It is powered by a dynamic, AI-driven core that builds an evolving profile of each entrepreneur and their business, ensuring every interaction is firmly based in their context and working towards their goals.Stage 1: Personalized Insight (The Cue)How it Works: Rather than only responding to inbound questions, the system proactively scans best practices including detailed country-specific knowledge bases, crosses them with the user’s situation and priorities, and proactively delivers new personalized ideas. These are single, targeted micro-insights framed as a simple "rules-of-thumb" to avoid cognitive overload.&nbsp; Basis: - Heuristic-Based Training: Simplified rules have been shown to increase profits by 8.1% in microenterprises, proving more effective than complex training. - Andragogy (Adult Learning Theory): Adults are motivated by solving immediate, real-world problems. This stage directly addresses their "need to know" and problem-centered orientation.Stage 2: Action Plan &amp; Asset (The Routine)How it Works: It then co-creates a short low-effort action plan with "if-then" scenarios to form a clear implementation intention. Friction is minimized by providing accompanying ready-made digital assets when possible (e.g., templates, schedules, content) that makes the behavior easy to perform. Basis: - Fogg's Behavior Model (B=MAP): Lasting behavior change comes from maximizing Ability (making it easy), in addition to building Motivation and providing the prompt.&nbsp; - Situated Learning Theory (Lave &amp; Wenger): Learning is most effective when it occurs in the context of application. Maia delivers the tool and the task directly into the entrepreneur's daily activities.Stage 3: Guided Reflection &amp; RewardHow it Works: Continuous structured follow-up prompts a supportive conversation to analyze results, learn from the experience, and celebrate the effort. This provides the immediate positive reinforcement that solidifies the actions as habits. Basis: - Personal Initiative (PI) Training: A focus on proactive mindset, error-learning, and opportunity-seeking has been shown to increase profits by 30%. The reflection stage is designed to coach this mindset - Kolb's Experiential Learning Cycle: This stage operationalizes "Reflective Observation," the critical step where experience is transformed into durable knowledge. - Duhigg's Habit Loop: The feeling of success and progress serves as the immediate "Reward" that tells the brain the entire loop is worth remembering and repeating.Stage 4: Adjustment &amp; AdaptationHow it Works: Insights from the reflection stage directly update the user's dynamic profile and inform the next cue. This ensures the next micro-insight is even more personalized, relevant, and impactful, creating a virtuous cycle of compounding gains. Basis: - High-Impact Consulting: The most effective entrepreneurial interventions evaluated in the literature are tailored and adaptive. Maia emulates this personalization at scale, a model proven to drive significant growth in SMEs.

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Impact Numbers

Context is King

MAIA @AMPYME Panama

Maia Overview Presentation

Part 2: Implementing this Architecture - MAIA's Coaching ...

Maia’s (Intellectual) Architecture: Situated Entrepreneur...