when the bottleneck is communication (coordination costs scale polynomial with number of nodes in the graph), the optimal strategy is to have fewer nodes working harder. If AI makes individual nodes more effective, then in terms of people we’re going to eliminate jobs and concentrate effort. The mean job effort (including the unemployed) may be halftime while the median is 996 and the mode is 0. Whether it works is more of a question of policy and how deflationary the technology is - if energy, water, food, shelter becomes too cheap to meter due to rapid technology advances, then i guess maybe that is how governments stave off revolution and survive? Otherwise - civil unrest, etc
the OO/FP fusion hypothesis resulted in a complicated language on the OO side (too complicated for enterprise application layer) and on the FP side an autistic culture war at the seam between FP frameworks. Functional Scala remains world class at high reliability services such as video streaming at Disney+ and Comcast, and Amazon search but not so much the Java everyman use case that I recall it being marketed for 15 years ago. And now the Scala leadership and the industry frameworks are pulling in different directions, Scala is academically funded.
companies outside the venture ecosystem need a lot more help. This is because they’re a lot harder to help. So, expect a Serenity Prayer situation. There is much less you can change. In return, you’re allowed to be older than 35. I would not say the work life balance is that different. bigger companies have deadlines and crises too. The crises are often worse because the management is looser.
yes but to validate it you need dynamic runtime logic and therefore a live server with all the I/O glue code that entails. i.e., static types alone cannot render your tax forms
i think you’re looking for the term “computational structure”, as in, “what is the computational structure of a user interface” i.e. what typeclasses does the computation reify. To avoid impedance mismatches the authoring notation must align exactly to and emerge from the underlying computational structure. So as a starting point: modern applications have a frontend and a backend, they are reactive, async, and concurrent, they perform network IO and manage resources. Or at least they have components that do, which means the computational structure as a whole must encode these capabilities. if the computational structure is not uniform, i.e. the frontend and backend are treated separately, or the database is relational but the backend-for-frontend needs dynamic graph walking, then you will have seams between modules and arbitrary glue code cruft will accumulate and this will violate the alignment between authoring notation and underlying structure. Now your ORM needs XML configs to inject additional knowledge about the data access patterns that can’t be reflected from the notation.
the request/response command/query nature of the REPL is what I am referring to. Great fit for RPC-oriented web backends backed by OLTP databases that start fresh each time and run to completion. Live scene editing seems closer in nature to a hot module reloading workflow, where we try to take care not to disturb long-lived objects and processes. PS, Jank is very cool. No idea what his plans are here and I’m not claiming a gamedev repl is impossible in any way.
legacy code generating lots of revenue will continue to pay well, there will continue to be low accountability to outcomes, managers will still make more money than individual contributors
lets call that stage 2 when the labor/ai spend drops below 1.0, to understand what that might look like i would compare to surgeon model. so like $500k for a Surgeon to manage outcomes with 10x AI leverage. Arguments for: managers are compensated proportional to the capital risk they are responsible for so it makes sense that as the leverage increases the comp increases, even if the ratio drops before it u-turns and climbs. Four arguments against: 1) the economy is going to look very different with different dynamic equilibrium in surprising places; 2) this assumes software best practices remain as they are today with no disruptive breakthroughs which is unlikely, 3) systems that promote inequality are vulnerable to constant attack so it may not be a stable equilibrium 4) it may not even work - code complexity scales faster than linearly with lines of code, where is the break even point and is it higher or lower on the complexity curve than the breakeven point today?
the investor bull case in AI is to cannabalize the labor markets at 15% margin, so 1:1 labor:AI budget is where we are headed next - e.g. $100k/100k for a senior dev. The AI share will come out of dev budgets, so expect senior salaries to fall and team sizes to shrink by a lot if this stuff works. Remember we’re in the land grab phase, all subsidized by VCs, but we’re speed running through the stages as and this phase appears to be ending based on twitter VC sentiment. There’s only so many times you can raise another $500M for 9 months of operating cost at -100% gross margin.
i kinda think we should blame the youtube alg for this, the algs set incentives which shape behavior at scale, and it’s not like one can make a living doing actual physics these days
tech layoffs have nothing to do with AI; the business has realized that they are not getting the expected marginal increase in returns for marginal headcount expansion, and while historically layoffs can cause brand damage and need to be avoided, the mainstream media is giving companies a pass because everybody is doing it
Hi Alex, if you have data that supports a positive Clojure growth narrative please publish it so that I and other consultants/influencers can share the good news in support of our shared mission. The perception of the decline of Clojure is becoming a board-level conversation at unicorn/ish size companies that are or were all-on on Clojure.