48 articles: AI strategy, autonomous agents, digital
sovereignty, FinOps, cybersecurity. Junyr Method™.
AI Agents Junyr Method™ Markets & AI 2027 AI-native Company Insights Cybersecurity Personal Effectiveness Transition Management Methodology Illustrative example
Lists of trigger words for AI agents circulate with claims their sources do not make. We checked them against the papers and current vendor guidance, then set out the ten action and effort keywords Junyr teaches and where each word belongs: prompt, tool or harness.
When code was expensive, buying packaged software was the right call. As agentic coding makes code almost free, building the management core in-house becomes the better investment and turns the tool into an asset, while market data and distribution stay external.
Agentic projects rarely pay back today, less because of the technology than because companies copy their human processes and organisation charts onto generalist models. What taking over failed projects taught us, and a three-step path: equip people, imagine the company, then give agents objectives rather than tasks.
Opus 5.5 cuts its price list by 20%, GPT-6 Sol halves its own, and for most business work the intelligence gap between frontier models is no longer visible. What the competition now runs on, what an agent task really costs, and where the frontier model still earns its price.
On one multi-agent development run, 19% of the cost went to subagent caches that expired while tests ran, and 8% to starting new agents. Five rules on waiting, spawning, reading, reporting and orchestrating, with the prices and Claude Code settings behind each one.
What an agent harness is, what a source-code audit of eleven production systems actually found inside one, and which of the figures circulating about agent failure can be sourced.
Why frontier labs can afford to slow down, what the 10% extinction figure really is, and what the remaining 90% leaves for a mid-sized company to build.
Why an AI-native company turns its quote into a simulator, and what twenty years of behavioural research say about how a buyer decides in front of one.
Decide in the morning, let agents execute in the afternoon, dictate to emit, read to approve: the personal-effectiveness techniques, with the measurements behind them.
GitHub repositories, generated projects and maintained products cannot be pooled: what their growth really changes for SaaS, procurement and governance.
A method for working with AI agents that separates exploration, human decisions and implementation, illustrated by seventeen days from Junyr's internal registry.
A Junyr field report: agents no longer access Git, while the earlier history, deployment images, backups and a decision registry each retain a distinct role.
HITL, HOTL and HOOTL: choosing the right supervision regime, enforcing executable limits and calibrating human escalation without mistaking statistical coverage for certainty.
Three interim orders clarify CSE consultation for AI projects in France: effects on work, pilots, replacement tools, expert support and the separate AI Act framework.
Email and office suites are not disappearing: organisations can reduce fragmentation by giving each channel a clear role and requiring interoperability, modularity and reversibility.
An AI feature alone is quickly copied; durable advantage comes from workflow integration, reliability, data, distribution and controlled unit economics.
A practical framework for assigning work to AI agents in deferred time: mandates, permissions, control points, accountability and measurement, without turning every employee into a manager.
Voice still matters, but unannounced calls are losing effectiveness: a practical method for assigning clear roles to messaging, video and controlled automation.
Spectateur, Artisan, Orchestre, Architecte, Pionnier: assess your SME’s AI maturity across nine dimensions using evidence and cumulative prerequisites.
A practical method for deciding on jurisdiction, source-code data, cybersecurity, total cost and post-quantum migration without treating cloud and on-premise as doctrines.
Tool-first choices, aimless PoCs, an isolated sponsor, poorly measured value and unprepared data: five observable risks and the decisions that control them.
INDUSTEC is an illustrative example for scoping an AI quotation assistant, measuring time, quality and adoption, and calculating ROI while keeping released capacity separate from cash savings.
A practical framework for combining cooperation and bargaining power: a real BATNA, reservation point, justified anchor, verifiable consequences and a way back.
A practical method for defining the role, making the process transparent, assessing comparable evidence and presenting a realistic employment proposition.