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Authors

Wasyra Engineering

Modernization, architecture, and reliable delivery

Wasyra Engineering documents patterns for moving legacy systems without freezing delivery or breaking ownership.

Focus areas

LegacyRefactorArchitecture

Posts by this author

Engineering

AI legacy migration: seven parity gates

A high benchmark score does not authorize a legacy migration. Seven gates turn code translation into evidence of parity and rollback.

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Engineering

Local AI for coding agents: five boundaries you need to measure

Running the model on device does not make the whole agent offline or secure. These five boundaries turn the local promise into a verifiable decision.

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Engineering

ReviewBench: how to evaluate a code review agent

Five decisions for measuring a code reviewer with representative PRs, auditable ground truth, honest metrics, and production validation.

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Engineering

Ephemeral credentials for agents: what changes with GitHub Apps

Five gates for letting an agent operate on repositories with short-lived tokens, least privilege, safe transport, and verifiable recovery.

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Engineering

GPT-6 prompt caching: how to measure cost and latency

GPT-6 adds prompt-caching diagnostics and controls. Five decisions for reducing repeated work without hiding costs, failures, or isolation.

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Engineering

Hybrid physical AI: what inference should stay on the robot

Microsoft proposes offloading robot inference to edge or cloud. Six decisions for gaining capacity without handing safety to the network.

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Engineering

Claude Opus 5.5: how to migrate an agent without breaking it

Claude Opus 5.5 changes reasoning, tools, and progress. Five gates for migrating agents with evidence, controlled cost, and rollback.

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Engineering

Grok 4.7: how to preserve reasoning across agent turns

Grok 4.7 changes state handling in the Responses API. Five criteria for preserving context, evaluating continuity, and controlling integration risks.

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AI Systems

AGENTS.md in Claude Code: how to validate a migration

Claude Code adds AGENTS.md support. Five criteria for sharing instructions while preserving scope, reproducibility, and control over changes.

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Engineering

Copilot Code Review: evidence to require when AI runs code

Copilot Code Review expands its shell tools. Five criteria to verify findings, constrain access and evaluate reviews through reproducible evidence.

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AI Systems

OpenAI Agents API: controls for long-running agents

The Agents API beta brings Codex infrastructure to applications. What to evaluate about state, permissions and recovery before operating agents.

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Engineering

Copilot Auto: evaluating cost and quality for your team

GitHub adds preferences to Copilot Auto. A practical framework for testing real tasks, measuring rework and deciding when to escalate review.

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Engineering

B2B SaaS technical due diligence checklist before you invest

What to review in architecture, security, data, debt, observability, and delivery before buying, investing in, or scaling a B2B SaaS.

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Engineering

Legacy modernization roadmap for SaaS without slowing the business

How to split SaaS modernization by routes, contracts, data, and operations to reduce risk without freezing sales or delivery.

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Engineering

Platform Engineering in 2026: why Gartner says 80% of large enterprises now run an IDP

Pure DevOps hit the ceiling. The new normal is an IDP with golden paths, embedded AI, policy-as-code, and FinOps as part of the pipeline. What to build and when.

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Engineering

Code agent benchmarks in 2026: why SWE-Bench Pro brings expectations back to earth

Top models hit 70%+ on SWE-Bench Verified and just 23% on SWE-Bench Pro. How to read these numbers before committing budget to an agent.

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Engineering

Developer experience in 2026: from IDE to agent-collaborative environment

The copilot moved from IDE feature to permanent colleague. Team metrics shifted from velocity to time in flow + clean-review rate.

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Engineering

Lakehouse in 2026: Iceberg, streaming, and why your warehouse falls short

Apache Iceberg won. CDC with Debezium, Flink streaming, and catalogs like Polaris or Unity are the new spine. What to keep, what to adopt, and what to measure before migrating.

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Engineering

LLM observability in 2026: why OpenTelemetry and evals must run together

Monitoring an LLM is not monitoring a microservice. Tokens, cost, variable latency, drift, and subjective quality. How to build the stack with OTel + GenAI semantic conventions + online evals.

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Engineering

Legacy modernization without freezing delivery

Most large refactors fail because they try to clean everything at once. The useful approach decouples risk, routes, and ownership.

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