Lock In App Uses Friction-Based Blocking to Help Users Reclaim Focus Time

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A productivity app called Lock In aims to address what its creators describe as 'time blindness' — the gap between intending to work and actually doing so. Unlike conventional focus apps that hard-block distractions, Lock In introduces a hold-to-unlock mechanism requiring users to press and hold a button for 3 to 10 seconds before accessing blocked apps. This brief pause is designed to engage the rational brain and prompt a conscious choice, rather than allowing reflexive phone use. Users can customize which app categories to block per session, while Android users can enable a whitelist mode that restricts everything except selected productive apps. The app's core features are available entirely free, positioning it against paid competitors such as Opal and Freedom that charge up to $100 per year.

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Teen founders skip graduation to join SF accelerator, building AI efficiency startup

James Yang and Anish Paleja, both 18-year-old Canadians from Ontario, skipped their high school graduation to attend Founders Inc.'s Off Season II accelerator in San Francisco. The two met at a Major League Hacking hackathon at age 15, when neither could code nor had any product development experience. They have since founded Brevitas, a startup focused on reducing token waste in multi-agent AI systems to help companies cut costs on AI workflows. Despite the program being only six days old, the pair say they have already achieved roughly six months' worth of progress. Both are prolific hackathon participants, with Paleja having attended 36 and Yang 14 in the past year alone.

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How to Systematically Read and Audit a Solidity Smart Contract You've Never Seen

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Google DeepMind VP Says He Has Stopped Writing Code, Hands Off to AI Agents

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Anthropic Research Pushes Spec-Driven AI Orchestration Over Prompt Engineering

Anthropic's engineering team has published research arguing that the infrastructure surrounding AI models matters as much as the models themselves, coining the term 'harness engineering' to describe this discipline. The research highlights recurring production failures including context degradation, over-ambitious single-pass agents, and unreliable self-evaluation in deployed systems. As teams scale from a handful of workflows to dozens, manually managed scaffolding breaks down and coordination overhead grows nonlinearly across multi-agent setups. The proposed shift moves away from bespoke prompt-based harnesses toward specification-driven contracts that define deliverables, verification criteria, agent assignments, and cost controls in structured but plain-English terms. Predicate Ventures' Blake Aber argues this declarative approach mirrors how Terraform and Kubernetes transformed infrastructure management, potentially compounding efficiency gains across entire product portfolios.

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