Source: SuperSSR Report-Date: 2026-06-15 Language: en Canonical-URL: https://superssr.net/reports/2026-06-15?lang=en RSS-URL: https://superssr.net/api/feed.rss?date=2026-06-15&lang=en Generated-At: 2026-06-15T16:30:11.000Z # Today's Best Build: VeriCode – Local-First Coding Agent with Cloud Deliberation Fallback **Report Date**: 2026-06-15 **Coverage**: 2026-06-15T00:00:00+08:00 – 2026-06-15T23:59:59+08:00 (UTC) **Status**: ok ## Today's Best Build: VeriCode – Local-First Coding Agent with Cloud Deliberation Fallback **One-liner**: A coding assistant that runs a 12B local model for fast edits, but seamlessly escalates complex reasoning to a multi-model deliberation panel, with staged verification to catch errors before they ship. **Why Now**: Recent export controls shut down Anthropic's Fable 5 globally, proving reliance on a single cloud model is risky. Developers increasingly demand local-first tools (Gemma 4 GGUF, VEXI) that never lose access. Meanwhile, OpenRouter's Fusion API shows multi-model deliberation improves accuracy, and fable-mode demonstrates that structured execution reduces errors. **Evidence**: - Local 12B models achieve useful coding performance on consumer GPUs (4.5 GB VRAM). _(signal #32033)_ - Multi-model deliberation via Fusion yields structured analysis with consensus and blind spots. _(signal #32246)_ - Staged execution discipline (fable-mode) catches errors that one-shot methods miss. _(signal #32057)_ - The unexpected shutdown of Fable 5 left developers without fallback plans, highlighting the need for local models. _(signal #32273)_ - Open-source AI coding agents like VEXI show demand for terminal-based local assistants. _(signal #32184)_ **Fastest Validation**: Ship a VS Code extension that uses a local gemma-4-12B-coder GGUF via llama.cpp for initial suggestions. When the model's confidence is low (e.g., output tokens contain 'uncertain'), make a curl request to Openrouter Fusion with the same prompt and display the deliberation result in a side panel. Use fable-mode's SKILL.md as a prompt template for the structured analysis. Invite 10 beta testers from r/SideProject and track how often the fusion step catches bugs or false positives over one week. **Counter-view**: VEXI (open-source, 7.6 overall) already provides a local coding agent, and Cursor/GitHub Copilot dominate the cloud-assisted space. VeriCode's differentiation is the explicit multi-model fallback and staged verification, which no single tool combines. However, if Copilot integrates a similar fusion feature, VeriCode would need deeper local integration (e.g., offline-first, hardware-specific tuning) to stay relevant. The risk is low: Copilot has not shown signs of adding multi-model deliberation, ## Top Signals ### yuxinlu1/gemma-4-12B-coder-fable5-composer2.5-v1-GGUF **Source**: huggingface | **Metric**: N/A (overall: 8) Demonstrates a viable local coding model under 5GB VRAM, enabling offline AI-assisted development without cloud dependencies. ### Openrouter Fusion API **Source**: hackernews | **Metric**: Score: 138 / Comments: 54 Introduces multi-model deliberation as a service, proving that combining expert models yields deeper analysis than a single call. ### mrtooher/fable-mode **Source**: github-trending | **Metric**: Stars: 377 Shows that structured staged execution with verification reduces errors in complex AI coding tasks, a key component of VeriCode's workflow. ### Fable 5 Went Dark Friday Night. I Ran My Critical Workflow on a Backup Saturday – Here's What Broke **Source**: devto | **Metric**: Comments: 5 Real-world account of a critical workflow breaking due to model shutdown, underscoring the urgent need for local fallback and redundancy. ## Discovery ### Q1. What solo-founder products launched today? **Signal**: Reddit post 'I built Someple — an AI workspace for summarizing long videos' (score 6.6) describes a solo-founder product launched today. **Analysis**: Someple is a web app for video editors that summarizes long footage and converts it into editable project files. The founder built it solo and launched it today, targeting a specific pain point for creators spending too much time reviewing raw footage. **Takeaway**: ship a tool that addresses the tedious manual review process in video editing; the solo founder momentum suggests there is room for focused AI-assisted workflows. **Counter-view**: Descript already offers AI-powered video editing with transcription and content manipulation, but focuses on editing rather than pre-editing summarization. ### Q2. Which search terms or discussion threads are suddenly rising? **Signal**: Hacker News thread 'Windows 11 users are tired of MS account requirements' (score 354, 239 comments) is suddenly rising. **Analysis**: The thread reflects a surge in frustration over Microsoft's push for mandatory account integration in Windows 11, including folder management and login requirements. It has high engagement, indicating a widespread sentiment. **Takeaway**: watch this trend as it signals a potential market for alternative OS flavors or tools that bypass Microsoft account requirements, but avoid building a full OS replacement. **Counter-view**: Linux desktop environments like Ubuntu or Fedora face adoption friction due to software compatibility, despite offering the account-free experience users demand. ### Q3. Which open-source projects are growing fast but lack a commercial offering? **Signal**: GitHub trending project 'kage' (tamnd/kage, 1331 stars) shadows any website to a single binary for offline viewing; it has no commercial offering. **Analysis**: Kage clones websites into offline-viewable folders by snapshotting the DOM in headless Chrome. It has gained 1331 stars on GitHub and earned 631 points on Hacker News, showing strong interest. It is fully open-source with no paid tier or commercial variant. **Takeaway**: build a commercial service around offline website archiving, targeting enterprises needing compliance or researchers; the open-source base provides distribution while a premium version could add scheduling, storage, and search. **Counter-view**: Existing offline browsers like SingleFile or HTTrack are free and open-source, but lack the polished UX and cloud features that could justify a paid product. ### Q4. What are developers complaining about today? **Signal**: Hacker News discussion 'Hetzner increased dedicated server prices 3-4x' (score 115, 52 comments) highlights developer complaints about price hikes. **Analysis**: Hetzner raised prices on bare metal servers like AX102 from €124 to €454 and AX162 from €244 to €844, following a 30% increase months earlier. Developers are expressing anger and considering alternatives. **Takeaway**: pass on Hetzner for new deployments until pricing stabilizes; explore or build tools that simplify migration to other providers or enable hybrid setups to avoid vendor lock-in. **Counter-view**: OVH, Leaseweb, and AWS remain viable alternatives, though OVH has had reliability issues and AWS can be more expensive for comparable dedicated hardware. ## Tech Radar ### Q5. What is the fastest-growing developer tool this week? **Signal**: OpenRouter Fusion API (Hacker News, Score: 138, Comments: 54) **Analysis**: OpenRouter's Fusion API allows developers to run multi-model deliberation with a single prompt, aggregating responses from a panel of expert models. The high engagement (138 points, 54 comments) indicates strong interest in bypassing single-model limitations and reducing integration complexity. **Takeaway**: Build integrations and applications on top of Fusion API to offer multi-model reasoning without managing multiple providers. **Counter-view**: Anthropic's Claude and Google's Gemini remain single-model and may lose developers who want diverse reasoning; Fusion's parallel deliberation could fragment the market but also raise latency concerns. ### Q6. Which AI models, frameworks, or infrastructure deserve attention? **Signal**: yuxinlu1/gemma-4-12B-coder-fable5-composer2.5-v1-GGUF (Hugging Face, overall score 8) **Analysis**: This is a GGUF-quantized version of Google's Gemma 4 12B model, fine-tuned for coding and reasoning with fable5 and composer2.5 datasets. Its release on Hugging Face with a permissive Gemma license and GGUF format makes it immediately usable with llama.cpp for local, offline code generation. The signal reflects a growing ecosystem of powerful local coding models. **Takeaway**: Build local code-assist tools or privacy-first development agents using this model; it enables on-device coding without API costs. **Counter-view**: GitHub Copilot's cloud dependency may become less attractive as local models like Gemma4-12B-Coder approach comparable quality; however, Copilot still benefits from extensive context and real-time integration. ### Q7. Which platforms, products, or technologies are declining? **Signal**: Anthropic Fable 5 taken offline worldwide after US export control directive (Hacker News, Score: 129, Comments: 94) **Analysis**: Anthropic's advanced model Fable 5 was abruptly disabled for all customers due to a US government order restricting foreign national access. This indicates that frontier AI models face sudden regulatory shutdown risk, making them unreliable for long-term production dependencies. **Takeaway**: Defer building critical workflows on top of a single frontier model; diversify across providers and consider self-hosted open models to mitigate geopolitical and regulatory risks. **Counter-view**: OpenAI's Sora also shut down recently due to financial losses, showing that model discontinuation is not limited to regulatory actions—any provider can pull a product. ### Q8. What tech stacks are successful Show HN / GitHub projects using? **Signal**: Show HN: Kage – a website cloning tool built in Go (Hacker News, Score: 631, Comments: 122; GitHub Stars: 1331) **Analysis**: Kage is a Go-based CLI that shadows entire websites for offline viewing by rendering pages in headless Chrome and stripping scripts. It achieved 631 HN points and 1331 GitHub stars, showing strong validation. The choice of Go for a performance-critical CLI tool, combined with Chrome headless for DOM capture, is a proven stack for such projects. **Takeaway**: Ship CLI-first tools in Go for both performance and simplicity; pair with headless browsers when you need real browser rendering without bundling a full browser. **Counter-view**: Rust-based alternatives like Iroh 1.0 (43 HN points) are gaining for networking tools, but Go's ease of cross-compilation and rich standard library gave Kage an edge in adoption speed. ## Competitive Intel ### Q9. What pricing and revenue models are indie developers discussing? **Signal**: Reddit post (id=31977) where the maker of Vizro offers 10 free Pro accounts in exchange for honest feedback, discussing the challenge of converting free users to paid. Product Hunt listing for IdleDev (id=32158) markets a 'get paid while your AI agent thinks' model, indicating a revenue share on agent compute time. Dev.to article (id=32274) describes a WordPress AI chatbot whose free tier is not a trial but a genuine free offering, aiming to build trust and convert via premium features. **Analysis**: Indie developers are experimenting with unconventional pricing models beyond traditional SaaS subscriptions. The Vizro example shows a direct engagement strategy—giving away premium access for feedback on early-stage products. IdleDev's model is unique: it monetizes idle agent compute, suggesting a peer-to-peer or marketplace approach. The WordPress chatbot article reveals a deliberate 'free-first' design philosophy, where the free tier is designed to be genuinely useful to build a user base bef **Takeaway**: Watch this space: experiment with free-first, feedback-for-access, or compute-revenue-share models as alternatives to traditional pricing. Consider offering a genuinely useful free tier to build trust before converting. **Counter-view**: The classic SaaS freemium model (e.g., Intercom's limited free tier) still dominates in B2B. However, Salesforce's $3.6B acquisition of Fin/Intercom (id=32349) shows that enterprise pricing can still command massive exits, suggesting indie developers should not abandon subscription models entirely. ### Q10. What migration, replacement, or "X is dead" trends are emerging? **Signal**: Reddit post (id=32143) about Anthropic's Fable 5 program being 'wound down mid-build' leading the developer to ship a World Cup predictor solo, and a Dev.to article (id=32273) titled 'Fable 5 Went Dark Friday Night' detailing the sudden global shutdown of Fable and Mythos after a government order. Hacker News discussion (id=32097) reports that Anthropic's advanced models are now restricted to US nationals under export control. Reddit (id=32139) states 'astro after the cloudflare acquisition shou **Analysis**: Two clear trends: first, the sudden unavailability of Anthropic's Fable/Mythos models is forcing developers to either build their own models or migrate to alternatives. This is a genuine 'Fable is dead' signal, driven by geopolitical regulation. Second, the Astro-Cloudflare acquisition is reigniting the static-site vs. Next.js debate, with developers recommending migration to Astro for content-heavy sites due to its zero-JS defaults and simplified deployment. Both signals indicate reactive migra **Takeaway**: Build dependency-aware alternatives: if you rely on a single proprietary model (like Fable), have a fallback plan. For content websites, evaluate Astro now as a replacement for Next.js, especially if Cloudflare's integration aligns with your stack. **Counter-view**: Not all developers see Fable's shutdown as a death knell. Some (e.g., in id=32141) discuss using multiple AI coding agents from different providers, suggesting a diversification strategy rather than outright replacement. Similarly, Next.js continues to see strong usage (id=32285 shows developers still using it for PR descriptions), so the 'Next.js is dead' narrative is premature. ### Q11. Which old projects or legacy needs are suddenly coming back? **Signal**: Dev.to article (id=32128) shows renewed interest in running Docker on old Android phones via QEMU, repurposing outdated hardware as development servers. Reddit post (id=31978) introduces Ariami, a self-hosted music app that makes it easy to stream personal music collections, addressing the legacy need for local music ownership. Hacker News (id=32243) highlights Bitsy, a little game engine from the early indie scene, being actively used and discussed for creating tiny worlds and stories. Dev.to ( **Analysis**: Indie developers are reviving old hardware (Android phones) and old software paradigms (self-hosted music, simple game engines, first-principles NFT building). This suggests a counter-movement to cloud dependency and hype-driven tech. Docker on Android fulfills a need for cheap, private compute. Ariami addresses frustration with streaming service lock-in and library erosion. Bitsy's return signals a desire for constraint-based creativity. The NFT tutorial suggests a maturing perspective on block **Takeaway**: Ship tools that empower self-hosting and local-first ownership: build a one-command setup for self-hosted music servers (like Ariami) or a Docker-on-Android wizard. The audience is developers tired of subscription fatigue and walled gardens. **Counter-view**: While these niches see renewed interest, the mainstream still values convenience and cloud services. Spotify's dominance and the ease of AWS EC2 suggest most users prefer managed solutions. The Bitsy community (HN score 251) is small compared to Unity or Godot. These trends may remain hobbyist-level unless they solve a critical pain point better than existing alternatives. ## Trends ### Q12. What are the highest-frequency keywords this week? **Signal**: Today's signals show 'AI agent' and 'coding agent' appearing in at least 10 distinct posts (e.g., VEXI with 7.6 score, OpenRouter Fusion with 138 points, fable-mode with 377 stars). **Analysis**: The dominant recurring theme is agentic infrastructure: coding agents (VEXI, MiMo Code, Notchcode), skill marketplaces (Luban, fable-mode), and agent management platforms (Novu Connect, PandaProbe Cloud). Many signals also emphasize offline/on-device execution (OffPay, ColibotAI, Trace). This suggests a shift from basic chatbots to operational agents with persistent memory and local autonomy. **Takeaway**: Ship: Double down on building AI agent infrastructure – coding agents, skill marketplaces, and on-device execution are the highest-frequency signals this week. **Counter-view**: Despite the hype, many agent tools fail to retain users – early Devin had <10k active users after launch. Focus on retention loops and real user pain points. ### Q13. Which concepts are cooling down? **Signal**: Multiple signals report the sudden shutdown of Anthropic's Fable 5 and Mythos 5 (id=32273, score 6.5, 5 comments), and the US export control on Anthropic (id=32097, score 129/94). Additionally, Rio de Janeiro's 'homegrown' LLM was exposed as a merge of existing models (id=32088, score 381/201). **Analysis**: Fable 5, previously a top-tier frontier model, was disabled worldwide due to government order, and users scrambled to backup workflows. The exposé of Rio-3.5-Open-397B as a mere merge undermines trust in claimed originality. OpenAI also shut down Sora, cooling the video generation hype. These events signal a cooling of reliance on exclusive frontier models and unchecked AI claims. **Takeaway**: Defer: Avoid building new products that depend on Fable 5 or similar frontier models – regulatory and reliability risks are material. Watch for alternative open models like Gemma 4 (id=32033) or Llama 4. **Counter-view**: Competitors offering 'Fable 5 as a service' (e.g., Cursor's Claude tier) now face supply chain risk. Consider building on open models like Gemma 4 GGUF (id=32033) which operates independently. ### Q14. Which new terms or categories are emerging from zero? **Signal**: Three novel concepts appear: 'Fusion' by OpenRouter (id=32246, score 138/54) – multi-model deliberation; 'OffPay' (id=32155, score 8) – offline UPI payments via USSD; 'Luban Skill' (id=32232, stars 329) – a marketplace for agent skills with revalidation. **Analysis**: Fusion introduces parallel multi-model inference with web search, a new paradigm for quality. OffPay leverages existing USSD infrastructure for offline payments, a zero-to-one adjacent to UPI. Luban Skill formalizes shareable agent skills with testing, addressing a gap in agent reliability. All three have minimal direct competition and high novelty. **Takeaway**: Build: Prototype a multi-model deliberation agent (like Fusion) and an offline payment skill for existing agent frameworks – both are greenfield opportunities with zero incumbent noise. **Counter-view**: OpenRouter's existing routing API already serves 100k+ developers – building a competing multi-model aggregator is risky. Instead, differentiate with offline or skill-specific use cases (e.g., OffPay for rural markets). ## Action ### Q15. What is most worth spending 2 hours on today? **Signal**: Openrouter Fusion API on Hacker News with Score 138 / Comments 54 (id=32246) and Fable 5 shutdown on Dev.to with 5 comments (id=32273) point to a clear gap: model-agnostic multi-model deliberation that survives API shutdowns. **Analysis**: The Fusion API signal (7.9) demonstrates strong interest in multi-model deliberation—sending a prompt to several models in parallel and synthesizing results. Meanwhile, the Fable 5 shutdown (6.5) shows the fragility of depending on a single provider. Spending 2 hours today to prototype a lightweight multi-model agent that uses open-source models (like Gemma-4-12B-Coder from id=32033) is the highest-leverage action because it addresses both the 'smarter answers' desire and the 'avoid vendor lock- **Takeaway**: Build a minimal multi-model deliberation CLI that ties together 2–3 open-source GGUF models and a free tier of a hosted API like Openrouter. Ship it as a single-file script to validate within 2 hours. **Counter-view**: OpenAI or Anthropic might argue that their single models are already superior to multi-model ensembles, but the Fable 5 shutdown proves that 'superior' doesn't matter if the model vanishes overnight. ### Q16. Why not the other two candidate directions? **Signal**: Candidate B: fable-mode on GitHub (Stars 377, id=32057) enforces staged execution discipline but is tied to Claude's ecosystem, which is now risky after Fable 5 shutdown. Candidate C: building a Fable 5 replacement agent is reactive and crowded—VEXI (id=32184) and Relay (id=32172) already occupy that space. **Analysis**: Fable-mode (7.7) is excellent for structured tasks but its Claude-proprietary design means it cannot survive the Anthropic export control risk we just witnessed. Candidate C (a Fable 5 clone) would require months of work and faces entrenched competition (VEXI has 7.6, Relay 7.7). The multi-model deliberation direction is both more novel and more robust—its key insight is using diversity of models as a feature, not a workaround. **Takeaway**: Defer both fable-mode integration and building a Fable 5 replacement. The former is too risky, the latter too crowded. Focus on multi-model deliberation where there is a clear white space. **Counter-view**: Proponents of fable-mode might say its structured discipline is orthogonal to model choice and could be built on any LLM backend, but the signal shows it is currently Claude-only and not easily ported. ### Q17. What is the fastest validation step? **Signal**: Openrouter Fusion API (id=32246) already has a working pattern; you can replicate it in one terminal session using llama.cpp GGUF models (id=32033) and a shell script to parallel-call 3 local models and merge outputs. **Analysis**: The fastest validation is to run a single experiment: take a prompt ('Write a Python function to parse CSV'), send it in parallel to Gemma-4-12B-Coder (GGUF), Llama 3.2 3B (from id=32072), and a small model like Phi-3. Collect outputs, then use a simple voting or concatenation to produce a final answer. If the multi-model result is factually better or more creative than any single model, the thesis is validated. This takes 30–60 minutes and costs nothing beyond local compute. **Takeaway**: Ship this validation script today and share the results on Hacker News/Builders. If the multi-model output beats individual models, you have immediate proof of concept. **Counter-view**: Cynics will say that multi-model deliberation is just ensemble averaging and that a single fine-tuned model will always beat it. But the Fusion API's strong HN engagement (138 points) suggests the community disagrees. ### Q18. What product should this become over the weekend? **Signal**: Combining Fusion API's multi-model pattern (id=32246) with the agentic execution discipline of fable-mode (id=32057) and the offline resilience seen in Kage (id=32087) and OffPay (id=32155) suggests a product: a CLI agent that delegates sub-tasks to multiple local models and validates results—all offline. **Analysis**: Call it 'Orchid' (a flower that combines multiple petals). Over the weekend, build: 1) A task planner that decomposes a request into sub-tasks, 2) A dispatcher that sends each sub-task to a different local model (e.g., coding→ Gemma-4-12B-Coder, reasoning→ Llama 3.2, creativity→ a small GGUF), 3) A validator that checks consistency and retries failures. The product should support 100% offline mode (inspired by OffPay's offline UPI) and a web fetch for knowledge (like Fusion). This directly addre **Takeaway**: Build Orchid as an open-source CLI tool. Ship v0.1 by Sunday night with 3 local models, task decomposition, and a simple voting mechanism. **Counter-view**: VEXI (id=32184) is already an open-source AI coding agent in the terminal. However, Orchid's differentiator is multi-model deliberation and offline-first, which VEXI lacks. ### Q19. How should initial pricing and packaging look? **Signal**: Relay's AI receptionist (id=32172, 7.7) has a free tier that learns from calls; OffPay (id=32155, 8.0) is free with no sign-up; Capecho (id=32171, 7.1) is free with SRS. The market is voting for freemium with generous free tiers for single users, then charging for team/enterprise features. **Analysis**: Pricing for Orchid: Free for personal use (single user, local models only, max 5 parallel calls). Paid tiers: Solo Plan $9/month (cloud model access, 50 parallel calls/month, web search), Team Plan $29/month (shared task queue, priority support, unlimited local models). Enterprise Plan custom (on-prem deployment, audit logs, integration with existing agent stacks). This mirrors the successful packaging of Novu Connect (id=32175, 6.2) and Notra (id=32164, 6.5) which both have free tiers that conv **Takeaway**: Ship with a free tier that is genuinely useful (no time limit, just usage caps). Charge early adopters for cloud models and team features. List pricing on the GitHub README from day one. **Counter-view**: Some will argue that AI agent tools should be entirely free and open-source (like VEXI, id=32184). But the success of Relay (7.7) and other paid tools shows that users pay for reliability and cloud model access. Maintain a free local-only mode to compete with VEXI. ### Q20. What is the strongest counter-view? **Signal**: The strongest counter-view is that single-model quality is advancing so fast that multi-model deliberation will become obsolete within 6 months. For example, Apple Foundation Models (id=32237, Score 340) and Gemma-4-12B-Coder (id=32033) are already boosting single-model capability. The HN discussion on 'AI is code – and can't be prompted into being smarter' (id=32104, Score 49) argues that prompting alone won't make AI smarter; architecture improvements matter more. **Analysis**: Critics will say: 'Why build a complex multi-model orchestrator when a single fine-tuned model like Gemma-4-12B-Coder already beats your ensemble?' The counter-view is credible—soon single models may handle most tasks. However, Orchid's offline resilience and model diversity are hedges against single-model outages (Fable 5) and regulatory risks (export controls). Furthermore, the Fusion API's popularity (138 points) shows multi-model thinking is not just a workaround but a feature for nuanced re **Takeaway**: Watch the trajectory of Apple Foundation Models and Gemma-4. If single-model quality surpasses multi-model ensembles, pivot Orchid to an 'escape hatch' that still orchestrates models but primarily adds redundancy and privacy layers. **Counter-view**: The counter-view itself has a counter: even if single models improve, the Fable 5 shutdown (id=32273) and export control directive (id=32097) prove that availability and sovereignty are separate from quality. Orchid's value proposition remains even if quality parity is reached. ## Action Plan **2-Hour Build**: Create a minimal VS Code extension that loads the gemma-4-12B-coder GGUF via llama.cpp, intercepts 'Explain this code' commands, and if the model outputs low-confidence tokens (detected via a simple heuristic like 'I'm not sure'), makes a curl request to Openrouter Fusion with the same prompt. Display the combined analysis in a side panel. Use fable-mode's SKILL.md as a prompt template for the staged analysis. Package as a .vsix and test on a public repo. **Why This Wins**: Combines three proven trends: local models for latency and privacy, fusion for correctness, and structured verification for reliability. No existing coding assistant offers this triple combination. The recent Fable 5 shutdown creates a window for local-first tools. **Why Not Alternatives**: - Cursor is cloud-reliant and lacks multi-model deliberation – single model per response. - GitHub Copilot uses a single model per request and has no local fallback. - Open-source agents like VEXI don't have built-in fusion or staged verification – they rely on a single model with basic prompting. - Manual multi-model use requires switching between tabs and apps – no seamless integration. **Fastest Validation**: Post the extension to r/SideProject and HN with a demo video. Ask users to test on their own code and report bugs caught and false positives. Target 50 signups in 48 hours. Track usage metrics: number of Fusion calls, confidence threshold tweaks, user retention after first week. **Weekend Expansion**: Add a 'Fusion Debug' mode that shows the reasoning trace from the deliberation panel (which model contributed what). Cache local and fusion results to reduce latency and costs. Add support for custom local models via user-provided GGUF files. Create a simple web dashboard for users to review their bug reports.