BackboardIO

We’re building Backboard to help you route across models and manage context without rebuilding your stack. If you’re running into this, we broke it down here → backboard.io/blog/hidden-ch…

Hey chat, what’s been the hardest part of getting your AI system to actually work at scale? #BuildWithBackboard

What causes AI apps to break? It's not the model. It's infrastructure. Systems don’t remember, adapt, or route intelligently. Reliable AI needs memory + decision layers, not just API calls. If you’re building AI systems, this is worth understanding → backboard.io/blog/what-is-a…

What have you been building lately? We just made it a lot easier. Check out our API updates ↓ backboard.io/changelog/back…

Building AI infrastructure is hard. Doing it with the right people makes it a lot more fun. Meet the team behind Backboard— a group of people who all decided to build something that matters. 😁✌️ #BuildWithBackboard #AICommunity #TechTeam #StartupLife

Software isn’t just shifting from UI to API. It’s shifting from humans to machines as the primary user. Most systems today are still designed for people, but agents don’t need any of that. They need structured data, clear state, and something they can act on. What we’re starting to see in practice: Interfaces matter less. Interoperability matters more. Systems talking to systems. APIs instead of screens. The mistake is thinking this is just a frontend change. It’s not. If agents are executing workflows, then the real problem becomes: 🧠 how state is preserved 🔁 how context is carried forward ⚙️ how work progresses across steps Without that, every action is a reset, and agents never actually improve. This is where most teams get stuck. The demo works. Production doesn’t. Because what’s missing isn’t capability. It’s memory. We’ve been building Backboard around this idea: an API-first memory layer for agents to store and build on their work over time. If software is going to be used by machines … … it needs to remember like one. #BuildWithBackboard now.

Backboard API update — build AI systems in one call: 🧠 send_message endpoint — no setup, just start ⚙️ Unified API — threads, memory, tools handled automatically 🔧 Simplified tool outputs — no run tracking 🧩 Per-turn configuration — control every interaction 🧭 Docs + navigation overhaul — faster to build 🗂️ Full backward compatibility — no forced migrations Less plumbing. More product. #BuildWithProduct → backboard.io

The Force is strong with AI right now. And our founder, @RobImbeault, spoke about it at @TechTO (on Star Wars Day rocking his Star Wars tee) Software alone is no longer the moat. In a world where AI can generate code at lightspeed, shipping features isn’t your advantage anymore. Your moat is shifting to: • distribution & community • the founders and team • real, measurable outcomes Everyone can build. Not everyone can win. If you’re building in AI right now, it’s worth asking: Are you shipping features or building something defensible? Explore Backboard → backboard.io #BuildWithBackboard #AI #Tech #SoftwareEngineering

Can confirm! @RobImbeault

Software is starting to be designed for machines, not just humans. As agents take on more work, the primary user increasingly looks like another system. That shifts the design center from dashboards and clicks to APIs, state, and interoperability. The hard part is not giving agents an interface. It is giving them reliable access to context and work-in-progress over time. That is why memory matters. Agents need a persistent layer to store, retrieve, and build on prior work. The next important interface in software may not be a screen. It may be memory.

6 Backboard Releases You Can Use Today 🧠 Adaptive context management ⚖️ Memory tiers (Light vs Pro) 🧭 New navigation + organizations + docs overhaul 🧩 Custom memory orchestration per assistant 🔍 Manual memory search via API ⚙️ Portable parallel stateful tool calling backboard.io/blog/stateful-…

Everyone can build an AI demo. What’s the hardest part of getting it to actually work in production? #BuildWithBackboard

Your AI isn’t forgetful. It just doesn’t remember anything. Most AI products reset every interaction. No memory. No continuity. Just cold starts. So users repeat themselves. Context gets lost. Outputs drift. And everyone blames the model. But the real issue? No persistent state. Without memory, you’re not building intelligence. You’re replaying prompts. That’s the gap between demo AI and real AI.

Hallucinations aren’t just a reasoning problem. They’re a context problem. Most models aren’t “making things up.” They’re working with: • missing history • weak retrieval • incomplete state If the input is broken, the output will be too. The real unlock isn’t better prompts. It’s better memory. Reliable AI systems aren’t built in one turn. They’re built on: • preserved context • prior decisions • consistent state In production, this is where things fail: Context gets split Context gets dropped Context degrades And the system gets more confident while becoming less trustworthy. If you want dependable AI: Don’t fix hallucinations. Fix memory.

The durable value in AI is shifting below the app layer. Most products ride on models they do not control. What holds up in production is infrastructure: state, orchestration, observability, and portability. The hard part starts after the demo works.

Your AI team isn’t slow. They’re rebuilding the same infrastructure every other AI team is. Month 1: “we have a working demo” Month 3: “why are we still wiring memory, context, and model APIs?” The bottleneck isn’t the model. It’s everything around it: state memory orchestration cost portability The teams shipping fastest aren’t better at AI. They just stopped building the plumbing.

Not all tokens are created equal. The Hidden Challenge of Multi-LLM Context Management backboard.io/blog/the-hidde…

The risk of vendor lock-in! Built-in autorouting would solve this :)

Whoa! @ThePracticalDev Dev.to hosting a weekend challenge with some Backboard love 💕 @RobImbeault dev.to/devteam/join-o…

"Why Token Counting in Multi-LLM Systems Is Harder Than You Think" by @RobImbeault #DEVCommunity dev.to/robimbeault/wh…