November 2026 and Feb 2027 projections by extrapolating the recent doubling rates. Doubling times are taking ~4 months for the amount of human work time AI can perform. Another ~1.5–2× (3 months) to ~2–4× (6 months) increase in effective time horizon is a reasonable baseline expectation if trends hold. This points toward reliable multi-day (or longer) autonomous software/engineering-style tasks at moderate reliability becoming more common, with higher-reliability windows expanding into multi-hour continuous work.
There are parallel trends in harnesses/tools:Core model/agent capabilities.
Agents should handle more complex multi-step workflows, longer context/agency chains, and greater independence with less frequent human rescue. Reasoning, tool use, and self-correction continue improving; specialized or RL-tuned sub-agents for domain tasks become more practical.
Harnesses (scaffolding, orchestration, agent frameworks) will see further simplification and removal of current workarounds. Expect more native support for durable external state, typed/validated tool calls, bounded previews/references instead of dumping large outputs into context, executable control flow, multi-agent coordination, evaluation/feedback loops, and self-improving harnesses that adapt based on traces/PRs/logs. Enterprise-grade guardrails, cost routing (right model/reasoning level per task), sandboxing, and integration with company systems will mature.
AI applications and tools. Coding agents and “coworker-like” systems become even more central to engineering. Broader knowledge-work tools shift toward multi-skill agents executing real workflows (research, data analysis, ops, finance processes, etc.) with less hand-holding. Internal platforms, agent marketplaces/skills, and vertical applications proliferate; shelf life of tools continues to shorten (weeks rather than months). Adoption widens outside pure tech teams. Cost-efficiency and reliability improvements make production use more routine, though evaluation, data quality, and oversight remain critical bottlenecks.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.
