Heuristics to apply liberally when stuck
In one of the many collaborative sessions with various flavors of LLMs - in this case, Claude - I arrived at this list of heuristics. It seems like once you reach some early-mid point of your career in tech, you create a portfolio page (still to be done), and you put a post with your heuristics on it (now, done).
They lived in my personal notes for a few weeks, never to be published, but I caught myself coming back to them almost daily at work. All of them meta-game the approach to working with emerging tech; it seems they deserve to be here.
Just another interview question: any professional conundrum can be framed as a case study interview question, and those - being hypothetical and emotionless - are much easier to handle than the real-life scenarios. Apply to get yourself out of a conundrum with cold logic, experience, and without an emotional load clouding your judgement.
Friction Fulcrum: friction in a process increases overall quality. Too little leads to carelessness, too much is gridlock. Apply for a little extra motivation when dealing with pushback from stakeholders, an unreceptive market, or other ✨offputting✨ circumstances.
Cognitive Compost: Some ideas are scraps and peels. They need to decompose in the brain’s background processes to resurface as something innovative and useful. Apply when frustrated about wasted work that ended up going nowhere.
Skill Scaffolding: Learning is modular, especially in tech. Any new skills, even seemingly specific, are a modular block to quickly adapt to the next knowledge gap. Apply when unmotivated to learn a new skill that seems too specific or niche, or when demotivated by having to pivot to a new field.
Innovation Inertia: The bigger the past successes (or market share) of the organization, the bigger the resistance to change. A flavor of The Innovator’s Dilemma. Apply to protect sanity when building experimental projects in large organizations.
Collaborative Crystallization: Loose ideas align and form a cohesive strategy in a group setting. Apply when debating whether the half-baked idea is worth bringing up to the team.
Expertise Erosion: In the long run, overfocusing on one field of expertise - especially coupled with staying out of the loop on emerging tech and changing markets - makes you relatively obsolete. Apply when rolling your eyes at yet another AI headline.
Decisional Doppler Effect: the closer you are to decisions, the higher their urgency and importance seems to be. They’re usually not that important, or that urgent, and benefit from taking a breath and looking at the broader context. Apply when getting stressed out about work.
The next three posts, currently sitting defeated in my half-baked-and-unfinished queue:
The intersection of the California AI bill, and the impact of regulation on past technological breakthroughs
Innovating from first principles and this batch AI products
Calling The Peak of Inflated Expectations for AI
If you reply or comment with your pick, I will (most likely) actually finish it.