Louis-Paul Baril

Louis-Paul Baril Contact information, map and directions, contact form, opening hours, services, ratings, photos, videos and announcements from Louis-Paul Baril, Automation service, Montreal, QC.

Consultant IA Local & Sécurisé | J'aide les entreprises à implanter l'IA sans compromettre leurs données | Open Source & Automatisation | Ambassadeur du numérique de demain ayant pour mission: le partage de connaissance 🎯 Consultant IA spécialisé en solutions locales et sécurisées

J'aide les entreprises à adopter l'intelligence artificielle sans compromettre leurs données.

✅ Implémentation d'ou

tils IA open source
✅ Automatisation sécurisée des processus
✅ Formation et accompagnement d'équipes
✅ Stratégie IA sur mesure

🔒 Ma mission : Démocratiser l'IA tout en protégeant votre souveraineté numérique.

💡 Partage quotidien d'insights sur l'IA éthique et accessible.

📞 Parlons de votre projet IA.

Lately at HELPY Media, we've received a few client requests mentioning "ChatGPT" and "Google Gemini" as the "referring s...
03/23/2026

Lately at HELPY Media, we've received a few client requests mentioning "ChatGPT" and "Google Gemini" as the "referring sources". That might explain it 👍

Thanks to AEO Ranker 🚀

🧵 Building in Public: Solving the "Lost-in-the-Middle" ProblemJust shipped NEXT-46 to BusinessOS: Context-Aware Prompt A...
03/14/2026

🧵 Building in Public: Solving the "Lost-in-the-Middle" Problem

Just shipped NEXT-46 to BusinessOS: Context-Aware Prompt Assembly.

Here's what I built and why it matters 👇

The Problem:
When you feed an LLM a 50K+ token context (conversation history + docs + tools), models tend to ignore the middle. Critical info gets lost. Responses degrade.

This is the "lost-in-the-middle" phenomenon — well documented in research, rarely addressed in production systems.

The Solution:
I implemented a zone-structured prompt assembler that reorganizes context using the "sandwich" technique:

1. System instructions (top)
2. Most relevant context (early)
3. Full conversation history (middle)
4. Critical constraints + task (end)

Important info bookends the prompt. The model can't miss it.

What Changed:

• 800+ lines of implementation
• New context_assembler.py module
• Configurable modes (sandwich, chronological, relevance-ranked)
• Default: sandwich mode

Why I'm Sharing This:
Most AI platforms dump context blindly. I'm building a multi-tenant agent platform where reliability matters — legal, medical, enterprise. Can't afford hallucinations from poor prompt engineering.

Building in public means showing the unglamorous infrastructure work too. This isn't a flashy UI feature. It's the kind of thing that makes or breaks production AI.

What's Next:

• Usage tracking per org (BYOK support)
• Signed skills + guardrails

Yann LeCun just raised $1B to build AI that understands physics. Here's my prediction: we're about to witness the great ...
03/14/2026

Yann LeCun just raised $1B to build AI that understands physics. Here's my prediction: we're about to witness the great AI infrastructure fork.

While LeCun chases embodied AI that can fold your laundry and parallel park, the real disruption will happen in the boring stuff. Physical world understanding doesn't just mean robots—it means AI that can read your messy warehouse inventory, understand why your manufacturing line keeps jamming, or figure out why your HVAC system is bleeding money.

The kicker? This tech will democratize faster than anyone expects. Today's $1B research becomes tomorrow's open-source model running on a $5K server in your basement. We've seen this movie before—GPT-4 level capabilities now run locally on hardware that costs less than a decent workstation.

My prediction: within 18 months, we'll see physics-aware AI models that can troubleshoot real-world problems, optimized for local deployment. SMBs won't need to send their proprietary manufacturing data to the cloud—they'll run spatial reasoning models on their own infrastructure.

The companies betting everything on cloud AI dependency are about to get blindsided by businesses that own their AI stack. When your competitor can diagnose equipment failures in real-time without a single API call or monthly subscription, good luck explaining to your board why you're still renting intelligence.

Physical world AI + data sovereignty = the next competitive moat.

What physical world problems in your business could benefit from AI that actually understands space and matter?

Been heads-down on BusinessOS for the past few weeks, and the learning curve is... steep.I'm building an enterprise AI a...
03/13/2026

Been heads-down on BusinessOS for the past few weeks, and the learning curve is... steep.

I'm building an enterprise AI automation platform — the "OS layer" between employees' personal AI tools and company systems. Think: security, data sovereignty, compliance, telemetry on automation patterns.

What I'm grappling with:

Verticalization. Had a great conversation with Etienne Mérineau (Telegraph VC) last week. His advice hit hard: "Business OS" is too generic. Pick a vertical early — legal or medical. Long sales cycles, yes, but sticky customers and high compliance = real moat.

The cofounder question. I can build the tech. But I need someone product-oriented who can own GTM, talk to early customers, and shape the roadmap. Not just a CTO — a true cofounder who believes in the vision.

Building in public. Sharing the journey here because the alternative is building in silence and hoping it resonates. Reality check: enterprise sales are hard. Finding PMF is hard. But the problem is real — companies are drowning in AI tools with no governance layer.

Next: Deep-diving into legal tech as the initial vertical. Talking to lawyers, understanding their workflows, figuring out where AI automation actually moves the needle.

If you're in legal/medical ops and drowning in repetitive work — I want to hear about it. What would you automate first?

Just shipped 34,000 lines of code in one week building BusinessOS 🚀While most "AI startups" are making fancy chatbots, I...
03/12/2026

Just shipped 34,000 lines of code in one week building BusinessOS 🚀

While most "AI startups" are making fancy chatbots, I'm building something different - an actual operating system for how we'll work in the future.

The coolest part? The Commitment Trigger Engine that tracks every promise you make. When you tell a client "I'll get back to you Friday" in an email, the system remembers. No more dropped balls.

This isn't another AI assistant. It's infrastructure that actually understands your business and runs on YOUR servers - so you own your data forever.

What's the biggest promise you've accidentally forgotten this month? 😅

Drop a comment if you want to see what an AI-first business OS looks like!

Remember when ChatGPT first blew your mind? 🤯That was just the warm-up act.We've officially entered the "Agentic Era" - ...
03/11/2026

Remember when ChatGPT first blew your mind? 🤯

That was just the warm-up act.

We've officially entered the "Agentic Era" - where AI doesn't just chat, it actually DOES things. These new AI agents plan workflows, remember everything, and execute complex tasks across multiple systems without any hand-holding.

I just watched a client's AI agent automatically update 2000+ files, plan the sequence, and maintain perfect version control. Zero human intervention needed.

The shift is wild:
❌ Old AI: "Here's some info"
✅ New AI: "Done. Here's your completed result after 12 automated steps"

This isn't about replacing us - it's about freeing us from boring tasks so we can focus on the creative, strategic stuff that actually matters.

What's one repetitive process at your work that you'd love to hand off to an AI agent? I'm curious what everyone's dealing with! 👇

Just found out that visiting the wrong website could literally turn your AI assistant into a hacker 😳This actually happe...
03/10/2026

Just found out that visiting the wrong website could literally turn your AI assistant into a hacker 😳

This actually happened with something called "ClawJacked" - a vulnerability in OpenClaw (popular AI tool). Malicious websites could hijack your AI agents through a simple connection and turn them against you.

The scary part? No fancy hacking skills needed. Just click the wrong link and your helpful AI becomes a silent infiltrator on your own network.

Makes me wonder - how many of us are rushing to adopt AI tools without thinking about the security risks?

Have you ever checked the security settings on your AI tools, or do you just trust they're safe because they're "local"? 🤔

Just found out my "anonymous" Reddit account isn't so anonymous after all 😬New study shows AI can now match your writing...
03/09/2026

Just found out my "anonymous" Reddit account isn't so anonymous after all 😬

New study shows AI can now match your writing style to your real identity in minutes. That throwaway account where you vent about work? Your secret forum posts? AI can connect the dots.

Makes me think about all those times I thought I was posting privately... turns out our writing is like a fingerprint.

This hits different when you think about people who actually NEED anonymity - whistleblowers, activists, journalists' sources.

Anyone else feeling like privacy is becoming impossible? What do you do to protect yourself online?

Ever feel like you're feeding your business secrets to your competitors? 🤔Every time your team uploads sensitive docs to...
03/06/2026

Ever feel like you're feeding your business secrets to your competitors? 🤔

Every time your team uploads sensitive docs to ChatGPT or runs strategies through Claude, you're basically doing free R&D for Big Tech. They get smarter while you rent their intelligence month after month.

I'm building something different - AI that actually belongs to YOU. No cloud dependency, no data harvesting, no losing everything when you stop paying subscriptions.

Last month helped a client process 2,000+ confidential documents completely offline. Their team went from hours of manual work to instant answers - all while keeping every secret locked down tight.

What's one business process you'd NEVER trust to cloud AI? 👇

After 4 years building AI for enterprises with sensitive data, I got some hard truths from Etienne Mérineau at Telegraph...
03/03/2026

After 4 years building AI for enterprises with sensitive data, I got some hard truths from Etienne Mérineau at Telegraph VC that changed everything.

"Pick ONE vertical and dominate it," he said. I was trying to boil the ocean with a Business OS approach, spreading too thin across industries.

His reality check hit different:
• Sells don't lie - you need signed contracts
• Ship it - good enough is good enough
• Verticalize for sticky, long-term deals
• Founder-market fit actually matters

Then came the insight that crystallized my direction: Super individual contributors bring their own AI stack to companies. When they inevitably leave (18-24 months average), both sides lose everything.

The Business OS I've been building bridges personal workflows with company systems. Here's the kicker - we get telemetry on automation patterns, not the actual documents. Every deployment teaches the system new ways to eliminate repetitive work, making it smarter with each client.

That's the real moat. Not just another AI tool, but a learning system that gets better at giving people their time back.

Now I'm choosing my vertical. If you're in legal or medical tech dealing with data sovereignty requirements and AI adoption challenges, let's talk.

I'm building in public - no fake proof of concepts, just the real journey. Because after years of solving novel technical challenges for enterprises that can't risk cloud AI dependency, I know this problem is worth solving right.

Don't rent your AI, own it. 🔒

Last week, a conversation completely shifted my perspective on team building.After 10 VCs told me I needed a CTO to be t...
02/26/2026

Last week, a conversation completely shifted my perspective on team building.

After 10 VCs told me I needed a CTO to be taken seriously, I was stressed. I'd been hunting for that perfect PhD ML engineer, convinced that technical depth was my missing piece. Every pitch deck review ended with the same question: "Where's your technical co-founder?"

Then I met a CEO who just closed a successful round - no CTO on the team.

His words hit different: "Software is cheap now. Good product plus marketing is all you need."

At first, I pushed back. I'm building AI automation solutions for businesses handling sensitive data. Surely I need deep technical expertise, right? But as we talked, something clicked.

In the age of AI coding tools, the real moat isn't writing perfect algorithms - it's understanding what customers actually need and getting it in front of them.

Don't get me wrong. I need brilliant people. But maybe not a traditional CTO.

What I really need is someone who thinks in products, not just code. Someone who's been through exits and understands that the best technical solution means nothing if customers don't adopt it. Someone who can bridge the gap between what's technically possible and what actually solves real business problems.

This realization came at the perfect time. I've been so focused on the technical complexity of building local, air-gapped AI systems that I almost lost sight of why businesses need them in the first place. They want to automate their recurring tasks WITHOUT giving up control of their data. They want to own their AI, not rent it.

The technical challenges are real - building RAG pipelines, managing vector databases, creating systems that work without cloud dependencies. But these are solvable problems. The harder challenge is understanding which automation opportunities will actually move the needle for each client.

I've seen too many AI companies build impressive demos that never translate to real business value. They optimize for technical elegance instead of customer outcomes. They focus on what's possible instead of what's profitable.

Maybe what I need isn't someone who can architect the most sophisticated ML pipeline. Maybe I need someone who can look at a business process and immediately see where 2 hours of daily manual work can become 2 minutes of automated magic.

Someone who understands that the goal isn't to build AI - it's to give people their time back so they can focus on work that actually matters.

If you're a product person who's been through the journey of building something people actually want, and you believe businesses deserve to own their AI infrastructure instead of renting it forever - let's talk.

The future belongs to those who can translate AI capabilities into real business impact. Technical depth matters, but product intuition might matter more.

Why are Microsoft and IBM suddenly racing to build SMALLER AI models?The answer will change everything you think about A...
02/25/2026

Why are Microsoft and IBM suddenly racing to build SMALLER AI models?

The answer will change everything you think about AI.

While everyone's obsessing over bigger models, the real revolution is happening with Small Language Models (SLMs). Microsoft just dropped Phi-4 Multimodal and Phi-4 Mini (3.8B parameters), while IBM countered with their open-source Granite 3.2.

Here's what they know that most don't:

**Edge computing is the future.**
These smaller models run locally on your hardware. No cloud dependency. No subscription fees. No data leaving your premises.

**Performance vs. Size breakthrough.**
Phi-4 Mini delivers chat capabilities with 3.8 billion parameters - a fraction of GPT-4's size but handles most business tasks perfectly.

**Enterprise reality check.**
Most companies don't need trillion-parameter models to automate document updates or process internal communications. They need reliable, secure, LOCAL solutions.

IBM's open-source approach with Granite 3.2 is particularly smart - giving enterprises full control over their AI stack without vendor lock-in.

This isn't about building the biggest AI. It's about building the RIGHT AI for real business needs.

The companies winning tomorrow won't be those renting the most expensive cloud AI. They'll be the ones who own their intelligence infrastructure.

**Don't rent your AI, own it.**

What's your take on the SLM vs. LLM debate? Are you building for the cloud or the edge? 🤔

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Beaucoup d’entre vous me font parvenir leurs questions au sujet du marketing numérique et de la publicité Facebook. Comment faire ceci ou cela? Quelle est la meilleure technique? Comment mesurer le ROI? Le remarketing? Le ciblage? ...

Ça fait déjà plusieurs années que j’effectue la gestion de compte publicitaire Facebook pour toute sorte de clients, oeuvrant dans différentes verticales de marché et d’industrie. Malgré ma vaste expérience et les blueprint que je cumule (formations en publicité Facebook), j’en apprends tous les jours! Il faut savoir se renouveler sans cesse et ne jamais se lasser de tester de nouvelles tactiques.

Je veux en profiter pour échanger avec vous, qui désirez en savoir plus sur la publicité Facebook. Comment l’appliquer dans votre modèle d’affaires, comment créer des campagnes plus efficaces avec moins d’efforts, mener à bien une campagne de remarketing, etc. C’est avec grand plaisir que je m’engage à vous répondre et à cogiter publiquement avec vous sur cette page :)

Envoyez-moi vos questions via la messagerie Facebook. Ensemble, investissons dans le partage et l’économie de la connaissance!