AI insights
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What is the main takeaway from the article 'The Spiral Climbs: Ideas Are Expensive, Systems Are Cheap'?
The main takeaway is that design has evolved, emphasizing that while systems are inexpensive, ideas have become more costly. This shift highlights the importance of a connected stack and a rapid feedback loop to facilitate fast shipping and learning in design processes.
Topic focus: Core Claim -
What does the article suggest about the relationship between ideas and systems in design?
The article suggests that in the current design landscape, systems are cheap while ideas are expensive. This indicates a need for designers to focus on developing robust systems that can support innovative ideas efficiently.
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How does the article propose to improve the design process?
The article proposes using a connected stack and a 48-hour loop to ship quickly and learn effectively. This approach allows designers to iterate rapidly and adapt their ideas based on real-time feedback.
Topic focus: How To -
What is a key limitation mentioned in the article regarding the current state of design?
A key limitation mentioned is that while systems are readily available and inexpensive, the challenge lies in generating valuable and innovative ideas, which have become more costly. This creates a tension in the design process that needs to be navigated carefully.
Topic focus: Definition -
What is a practical application suggested in the article for designers?
The article suggests that designers should implement a 48-hour loop to facilitate rapid shipping and learning. This method encourages quick iterations and responsiveness to user feedback, enhancing the overall design process.
Topic focus: Definition -
What does the term 'connected stack' refer to in the context of the article?
In the context of the article, a 'connected stack' refers to an integrated system of tools and processes that work together to streamline the design workflow. This interconnectedness allows for more efficient collaboration and faster delivery of design solutions.
Topic focus: How To -
How does the article relate to the future of work in design?
The article relates to the future of work in design by highlighting the evolving nature of design processes, where systems are prioritized for their efficiency. This shift necessitates new roles and skills, as designers must adapt to a landscape where rapid iteration and learning are essential.
Topic focus: How To
In the evolving landscape of design and development, the focus has shifted from traditional methods to a more integrated, system-oriented approach. The journey from idea to code has become streamlined, with tools like Miro, Figma, and VS Code working together to enhance collaboration and speed. AI now plays a crucial role, assisting in everything from scaffolding to testing, while human oversight ensures quality and security. This modern workflow emphasizes critical thinking, empathy, and clear decision-making, allowing teams to adapt quickly and learn from their processes. As design becomes more intertwined with code, the challenge lies in maintaining clarity and connection throughout the development cycle.
History doesn’t loop; it climbs the same corners to a higher floor.
Late ’90s: function first. Ship it, paint it later.
2010s: design first. Cheaper dev, better tooling, design ran the room.
2025: systems everywhere: patterns are cheap, judgment is not, and speed finally has a brain.
The spine stayed the same: critical thinking, research, communication, empathy. What changed is distance. Idea to code is now a short walk. Live artifacts beat static decks, agents sit inside our tools, feedback lands faster, and excuses don’t.
What actually changed
Design isn’t dead; it moved to systems, tokens, and code. You still need taste and story, but you don’t need to redraw the same control for the hundredth time. Handoffs got shorter, prototypes run in the real stack, and decisions now link to artifacts and metrics, so nothing floats alone.
The modern stack I run (and how it’s all connected)
It’s a connected surface, not a pile of apps; each step hands context to the next.
- Miro to frame the bet, flows, and risks. One board. One narrative. It takes the hit: tons of drafts, sketches, ideas, docs, charts, all parked there. Organized, productive chaos.
- Figma, when I need to teach AI how to build it: states, constraints, edge cases. Pictures as instructions.
- VS Code + AI (Codex as my “dev team”) to scaffold, refactor, and test. AI is my pair, not my boss.
- GitHub for PRs and a clean decision log. Every change has a why.
- Jira for small, measurable bets. Throughput you can’t fake.
- Assistants embedded in the flow: Design Thinking Facilitator (personas/methods for bets), Systems Thinking Coach (loops, dependencies, second‑order effects), Meeting Minutes Facilitator (decisions, talk‑time analysis, auto‑actions into Jira).
Everything is connected.
Miro snapshot links to a Jira bet (goal, metric, exit).
Jira links to the Figma clarifier and the GitHub PR.
The PR holds the decision log and a preview.
Telemetry flows back into Jira and my debrief notes.
Design tokens match IDs in Figma Dev Mode and in code.
Smart commits update Jira. Meeting actions open tickets automatically.
One chain of truth from idea, through shipping, to learning.
TCE: the wipeout and the rebuild
We lost the plot. Wrong bet. Slow signals. It hurts fast. We lost all app data and connections. We decided to start over from zero.
We chose zero. That made every step simpler to judge: does it get us learning by Friday or not?
I cut the ceremony. Kept the spine.
Short interviews, plus a bot trained on our past data that interviewed me for about four hours and surfaced gaps we’d missed. We pulled the data we already had and tightened the hypothesis.
Miro framed the new bet. Figma clarified the states so the agent wouldn’t hallucinate.
In VS Code, the AI laid scaffolds and tests. I edited. I owned it.
PRs landed early. Jira tracked the bet, the metric, and the exit condition.
We shipped behind a flag, watched the dials, and adjusted.
We got back to market. Not because research vanished. Because waste did.
From UX to Product
Titles follow the work.
When UI is commoditized, advantage moves upstream: framing the problem, sequencing bets, owning outcomes.
“Product Designer” fits.
Not just “make it pretty.” Own the value. Own the risk.
Design closer to code. Engineers closer to users. Fewer handoffs. Cleaner bets.
0 to 1: what AI is good for (and what it isn’t)
AI gets me from zero to one, fast. Scaffolds, test shells, variant ideas, quick refactors. I’m not saying we don’t need developers; I was one. Code is messy. Edge cases bite. Architecture matters. Performance isn’t free. Security is a profession. After we hit one, professionals take over the code to harden, scale, and secure it.
Use AI to explore and draft. Use people to harden and scale. That balance is the job.
The 48-hour operating loop
This cadence is simple on purpose; it keeps the room aligned and the work honest.
Observe.
Support logs. Analytics. Sales notes. Meeting Minutes Facilitator pulls the last decisions and open risks; flags who’s blocked.
Orient.
One Miro snapshot: goal, constraints, success metric, edges to test. Systems Thinking Coach maps loops and second‑order effects so we don’t fix one metric and break another.
Decide.
Write a small bet. Define the minimum test. Design Thinking Facilitator runs JTBD/HMW to shape the bet and the test plan.
Act.
Use Figma for AI clarity, create an agent plan, scaffold in VS Code, open a PR early, and run a 30-minute usability pass.
Review.
Ship behind a flag. Watch metrics. Log decisions in the PR and Jira. Meeting Minutes Facilitator scores the debrief (talk‑time, sentiment, decision clarity) and opens follow‑ups in Jira; Systems Thinking Coach flags second‑order effects before we scale.
Fidelity ladder: sketch, prompt, runnable prototype, then production.
If it isn’t linked, it isn’t real.
Guardrails so speed doesn’t lie
- Agent RACI. Who proposes, who approves, who owns failure.
- Tests and telemetry are non-negotiable.
- System sameness check. Break patterns when user value demands it.
- Weekly research touchpoints. Light. Consistent.
- Privacy and ethics. Opt-in recording. Off-the-record flags. Redaction by default. Clear retention.
Metrics that keep you honest
Lead: time to first PR, time to usable prototype, review latency, and preview coverage.
Quality: escaped defects, task success rate, and decision-log completeness.
Outcome: one north-star metric per bet.
Collaboration/meeting health (auto‑scored by the Meeting Minutes Facilitator): hygiene score, talk-time fairness, sentiment, decision clarity, % of meetings with actions, SLA on follow-ups.
Connection health: % PRs linked to bets, % bets with telemetry, design-token drift rate.
My thinking stack: custom assistants I use every week
They don’t replace people. They sharpen me.
Design Thinking Facilitator
Spins working personas on demand. Rotates methods (JTBD, “How Might We,” 2x2s, assumption maps) so I don’t tunnel. Outputs crisp prompts, concept boards, and test plans.
Systems Thinking Coach
Maps feedback loops and dependencies. Flags second-order effects before we commit. Gives me a one-page global picture.
Meeting Minutes Facilitator
Turns meetings into decisions: agenda, outcomes, owners, deadlines.
And it doesn’t stop at notes. It analyzes dynamics: talk-time distribution, interruptions, sentiment, quote capture, question-to-statement ratio, and decision clarity. It pulls risks and open questions into Jira. Tracks follow-ups.
Private coaching notes for me. Redacted summaries for the team.
Use them like teammates. I still make the call.
Start / Stop / Keep
Start
- Writing measurable bets in Jira with an exit condition.
- Opening a PR within 24 hours of deciding.
- Running a 30-minute usability pass before polish.
Stop
- Treating Figma as the source of truth for everything.
- Shipping without a hypothesis and a metric.
- Letting agents merge code.
Keep
- Real people. Real empathy. Real collaboration. Real interviews. Real data. Real stories that move stakeholders.
Close
Tools got loud. Judgment still wins.
Patterns are cheap. Ideas are expensive.
If you can frame a problem, test it fast, and keep a clean trail of why, you can rebuild anything.
Your move. How does your team’s 48-hour loop look today? What breaks first? Send it. Let’s compare notes.
“Plans are worthless, but planning is everything.”
— Dwight D. Eisenhower
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