Last week, the HexaHacks team made the trip to Las Vegas for CES 2026. This wasn't about flashy booths or product launches—it was about stepping out of the day-to-day build loop, reconnecting with familiar faces, and welcoming new team members into our ecosystem.

Why CES?

We sponsored CES travel for our engineering team with a clear goal: get a real on-the-ground read of where the industry is headed. When you're deep in product development, it's easy to lose sight of what's actually shipping, what's resonating with users, and where the technical leverage is moving in 2026.

CES gave us that reality check. From enterprise AI automation to consumer productivity tools, we saw firsthand what's working, what's hype, and where we should be focusing our efforts.

One of our biggest takeaways: there's a massive gap between what "looks real" in a demo and what actually works in production. A robot that works once under perfect conditions isn't production-ready. An AI agent that's 98% accurate isn't good enough when your task has ten steps. This isn't criticism—it's physics. And it validated everything we've been building toward at HexaHacks.

What We're Building

HexaHacks is focused on agentic software that actually works. Our current product lineup includes:

Delight - Enterprise AI Automation Platform

Our deterministic agent runtime converts expensive ReAct reasoning into certified JSON scripts. We're seeing 98% cost reduction, sub-100ms execution times, and 99.9% reliability across production deployments with Fortune 500 enterprises and fast-growing startups.

At CES, we connected with potential enterprise customers who are tired of unreliable AI agents and looking for production-grade solutions. The feedback? They need what we've built.

Sunday - AI Email Assistant

Built on our MAGK (Multi-Agent Knowledge Graph) framework, Sunday demonstrates our commitment to pushing for better software with advanced AI memory agents and intelligent automation. It's a unified inbox with AI-powered triage, smart summaries, task extraction, and human-in-the-loop controls.

Magic Excel - Emerging Project

We're exploring new territory with Magic Excel, bringing AI-powered automation to the tool that runs the business world. More details coming soon as we validate the direction.

The Meetup: Building in Public

On our last night in Vegas, we hosted a small dinner at Fogo de Chão. What started as an informal gathering turned into something bigger—31+ prospective guests showed interest, and we ended up with a great mix of builders, researchers, and industry veterans.

The strong turnout sent a clear signal: builders want technical, high-trust, action-oriented spaces to connect and collaborate. Not networking for networking's sake, but real conversations about what we're building and where the industry is headed.

Lessons from CES 2026

Here's what stood out:

1. Reliability > Features

Enterprise customers care more about systems that actually work than flashy AI capabilities that fail in production. We saw this across robotics, autonomous systems, and AI agents. The companies getting traction weren't the ones with the most impressive demos—they were the ones solving constrained problems with proven components and clear ROI.

One robotics demo we saw couldn't handle a simple real-world deviation: moving a trash bin a few inches required reconfiguring the entire system through an app. That's not a bug, it's a fundamental limitation. The winners in 2026 will be those who respect boundary conditions and design around them, not pretend they don't exist.

2. Speed Matters

Sub-100ms execution isn't just nice to have—it's becoming table stakes for real-time AI applications. Across CES, from chip manufacturers to platform providers, the message was consistent: next-generation architectures are delivering 3-5X improvements in inference speed while dramatically reducing compute costs. The world is accelerating, and latency is becoming a competitive moat.

This validates our architecture decisions with Delight. When you're running mission-critical workflows, every millisecond compounds. Speed isn't just about user experience—it's about enabling entirely new categories of real-time automation.

3. Memory is Critical

AI agents need to remember context, learn from interactions, and improve over time. One-shot reasoning isn't enough. This is why we built our MAGK (Multi-Agent Knowledge Graph) framework for Sunday—AI without memory is just expensive autocomplete.

Across the show floor, the most compelling demos weren't about raw intelligence. They were about systems that learned from previous interactions, adapted to user preferences, and built context over time. Memory infrastructure is becoming as important as compute infrastructure.

4. The Full Stack Wins

One of the clearest themes at CES was the shift from point solutions to integrated platforms. The companies getting the most traction weren't just selling hardware or software—they were offering complete stacks where hardware, software, and networking work together seamlessly.

We're seeing this in our own work. Delight isn't just an agent runtime—it's deterministic execution, cost optimization, self-healing architecture, and Learning Loop systems working as one coherent platform. The companies that win won't be the ones with the best model or the best infrastructure. They'll be the ones who integrate the entire stack.

5. Open Source is Infrastructure

The open source AI ecosystem has reached a tipping point. Major players are releasing complete model packages—not just weights, but data, training recipes, simulation setups, everything. We're seeing sophisticated models across embeddings, reasoning, and domain-specific applications becoming freely available.

This shift matters. When infrastructure becomes open, innovation moves up the stack. The value isn't in having a model—it's in what you build on top of it. This is why we're doubling down on application-layer innovation while contributing back to the ecosystem through projects like Sunday.

6. Edge Computing Enables New Categories

Edge computing devices showcased at CES are reaching a new threshold: 64GB+ of unified memory capable of running sophisticated models locally, with no cloud dependency. Combined with reasoning models that can operate in constrained environments, we're approaching an inflection point for real-time, local AI.

This has huge implications for privacy-first AI, offline-capable systems, and applications where latency to the cloud is unacceptable. The edge isn't just about mobile devices anymore—it's about bringing intelligence to where the data lives.

7. Simulation + Reasoning Changes Everything

A major theme in autonomous systems at CES: the shift from data collection to simulation. Leading companies are using reasoning models combined with high-fidelity simulation to make synthetic data as valuable as real-world testing. This is a fundamental shift: you're no longer bottlenecked by data collection. You're bottlenecked by how well you can model reality.

We're applying similar thinking to Delight. Our Learning Loop architecture uses simulation and certified execution traces to improve agent reliability without requiring massive real-world datasets. When you can simulate failure modes and edge cases systematically, you get to 99.9% reliability faster than trial-and-error in production.

8. Community First

The strongest signal at CES wasn't on the show floor—it was in the conversations with people building real products and solving real problems. The 31+ builders who showed up to our Fogo de Chão dinner weren't looking for networking—they were looking for technical, high-trust spaces to collaborate.

This tells us something important: the best companies aren't built in isolation. They're built in ecosystems where ideas flow freely, where people challenge each other's assumptions, and where execution matters more than pitch decks.

What This Means for HexaHacks

CES 2026 confirmed what we already believed: the AI industry is splitting into two camps. One camp is chasing AGI and building foundation models. The other camp is building production systems that enterprises can actually deploy. We're firmly in the second camp.

The winners won't be the companies with the flashiest demos or the biggest models. They'll be the companies that master execution: reliable systems, predictable costs, measurable ROI, and the discipline to say no to everything that doesn't serve that mission.

Here's what we're doubling down on:

• Delight: Pushing our deterministic agent runtime from 99.9% to 99.99% reliability. Every nine matters when you're running mission-critical workflows.
• Sunday: Expanding our MAGK framework to handle more complex memory architectures. AI that remembers is AI that compounds in value.
• Magic Excel: Validating product-market fit and building toward a late 2026 launch. Excel runs the business world, and it's time for it to get smarter.
• Prodicity: Training the next generation of AI builders who understand that reliability isn't just a feature—it's the foundation.

The Execution Year

2026 is the year when "looks impressive" stops being enough. The market is maturing. Enterprise buyers are getting smarter. The hype cycle is compressing. What matters now is what actually ships, what actually works, and what actually creates value.

This was the consistent message across CES keynotes: the companies winning aren't the ones with the best ideas—they're the ones shipping consistently, year after year. Execution beats innovation. Reliability beats features. Real-world deployment beats demo magic.

That's our north star. Not the flashiest product. Not the biggest announcement. Just relentless, disciplined execution on the fundamentals: reliability, speed, memory, and real-world value.

Join Us

If you were at CES and want to meet up, swap notes, or plug into the HexaHacks ecosystem, send us a message at ask@hexahacks.com.

If you're building AI systems that need to work in production—not just in demos—we should talk. If you're tired of AI agents that fail 2% of the time and need something you can actually trust, join our waitlist.

This year is about execution. Let's build something that matters.