Insights for running a business that doesn’t need you.
Practical operations and AI insights to help your business become easier to run, and less dependent on you.
How Do You Test An AI Agent Before It Touches A Live Business Workflow?
Test an agent with an eval set of 20-50 tasks from real work, sandbox the tools, run it in shadow mode beside your current process, graduate autonomy on evidence, and turn every failure into a permanent regression test.
9 min readYour AI Agent Doesn't Have a Memory. It Has a Context Window -- And That Is the Problem
Agent memory fails quietly: context degrades answers and one poisoned write persists. What to store, what to expire, and how to test the store.
9 min readA 1.3B Model Reads Your Scans. The Interesting Part Is the 2B Model Checking Its Work
OpenBMB released a 1.3B document parser alongside a separate 2B checker that scores OCR output and flags what a human must review, and the split is what makes document automation safe near financial records.
5 min readDeepSeek Open-Sourced the Engine Behind Its AI Service. The Interesting Part Is What It Kept
DeepSeek open-sourced DeepInfer, the engine behind its own AI service, and disclosed what it earns per GPU-hour. The parts that make those economics work stayed inside the company.
5 min readLocal AI or Seat Subscriptions: The Pricing Just Moved on Both Sides
OpenAI added $100 Premium seats and NVIDIA's DGX Spark rose 75 per cent in a year. What each route costs a 25-seat firm, and the register worth building before you commit either way.
7 min readLovable Moved Its Own Site Off Next.js. The 98.5% Figure Is the Story.
Lovable has moved its own 42-million-visitor website onto the same server-rendered hosting as its 70 million AI-built apps. The migration is engineering news; the 98.5% lift in traffic from AI tools after pre-rendering is the number owners should look at.
8 min readYour Agent Doesn't Need a Memory Layer. It Needs Its History Back.
A plain retrieval baseline over raw conversation history beat the tested agentic memory systems in six of seven benchmark settings, and took a fraction of the ingestion time. Measure the cheap baseline first.
6 min readOne Box, Five Models, and a Licence Problem
LocalRouter runs chat, speech, image and video on one NVIDIA DGX Spark with a sub-second voice loop. The router is Apache 2.0. The models are not, and the licences decide what a business can ship.
8 min readThe expensive model should stop typing: what the handoff research actually found
Escalating a cheap model's failed work up to a strong one recovers less than half the quality gap and multiplies cost. The favourable direction is the other way round: strong model plans, cheap model executes.
7 min readFive pillars, one question each
- Method
- How do data consolidation and task-specific AI agents work in an operating business?
- Adviser asset
- Which operational issues create diligence risk or owner dependency?
- Proof asset
- What data and system evidence will an acquirer need to trust?
- Outcome asset
- How can a founder-led business become more transferable?
- Technical asset
- How can AI be used safely in core workflows?