Pricing the service: subscription, per-resolution, outcome-based
Subscription, per-resolution, outcome-based. The pricing decision tree, the cost-of-goods math, and the free-tier question, closer for the operate series.
Exploring the echoes reverberating through time left by the technology of yesterday as we embrace the technology of tomorrow.
The customer view vs the consultant view: two surfaces, one product
One backend, two surfaces. Customer asks and gets an answer. Consultant supervises the queue, approves, denies, and mines for patterns.
Onboarding new tenants: the five-minute path from signup to working AI
When a consultant signs up, how do they get from 'I have secret sauce' to a live AI surface in five minutes? Onboarding as a first-class feature.
Bedrock model selection: pick on evidence, not vibes
Sonnet, Haiku, Opus, Llama. Picking the right Bedrock model per use case using evals, not gut feel, and knowing when to switch.
What I'd cut, what I'd keep: the actual MVP cutline
Closing the AI MVP series. What you can safely skip on day one, what you absolutely can't, and what the first 30 days of customers will teach you that nothing else can.
The downgrade pattern for cross-boundary data transfer
When data leaves a regulated universe for an analytics one, what crosses isn't the data, it's a downgraded version of it. Plain downgrade rules, enforcement, audit trail, and a human approval step for first-of-pattern transfers.
The hybrid sync pattern: how cloud and local actually talk
The wiring between a cloud AI product and a local Mac Studio. SQS for events, S3 for artifacts, EventBridge for schedules, signed manifests for the round-trip.
AI in the news — week of May 24, 2026
Google I/O ships Gemini 3.5, Antigravity 2.0 with a CLI that built a working OS in 12 hours, AI Mode at 1B MAU. Meta cuts 8,000 with a $21B CoreWeave bet behind it. BCG: AI data centres hit two-thirds of US home electricity by 2030. The Stratos campus moves; Florida's pipeline gets denser.
Deployment: IaC, CI/CD, environments, the minimum shape
The smallest setup that lets you ship an AI MVP without breaking things. CDK, GitHub Actions, three environments, migrations and secrets handled honestly.
The cost model: what you pay before you have customers
Runway math for an AI MVP with zero customers. What the AWS free tier actually covers, what bites you, and when local pays back.
Failure modes: graceful degradation when something's down
Bedrock rate-limited, the Mac Studio offline, the customer asking something the AI can't handle, the graceful degradation patterns that fall back to human-only without the customer noticing.
Observability and audit, not later
CloudWatch, structured logs, a real audit table, and trace IDs that follow a request through every Lambda hop and every back-office Mac Studio job. Day one, not a thing you bolt on later.