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Recraft is one of the most potent emerging threats to Superside's model. Here's why it's particularly dangerous compared to the other AI tools mentioned earlier.

What Recraft Is

Recraft is an AI-powered design platform founded in 2022 and headquartered in San Francisco, with only 1–10 employees. It raised a $30M Series B led by Accel in May 2025 (total funding: $42M), with backing from Khosla Ventures, Madrona Ventures, Nat Friedman, and Elad Gil. Despite its tiny team, it's positioned as one of the top-ranked text-to-image models available. recraft

Why Recraft Is Uniquely Threatening to Superside

Unlike Midjourney or DALL·E, which produce flat raster images, Recraft generates editable vector graphics — SVGs, icons, logos, and illustrations that designers can actually scale, recolor, and modify in their workflows. This is a critical distinction because: [oreateai](https://www.oreateai.com/blog/recraft-ai-navigating-your-creative-toolkit-in-2025-and-beyond/d6f7cbcd15d27b

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Conduit Today and in the Future

Conduit v1 → MCP + Figma Plugin (available today) — Designer

• 100% Figma access (best in class / industry-leader)
• Instant AI edit (best in class / industry-leader)
• Deep import/export (best in class / industry-leader)
• Advanced website export — page, theme, viewport (best in class / industry-leader)

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Superside (superside.com) is an AI-powered creative-as-a-service platform that uses AI to accelerate and scale design and marketing work for enterprise brands. Here's how they apply AI: superside

AI-Enhanced Design Services

Superside combines AI-certified creative talent with over 40 AI-powered workflows to deliver design work faster and at scale. Their team uses generative AI tools like Midjourney, ChatGPT, Leonardo.ai, and others throughout the creative process — from brainstorming and concepting to final production. This has resulted in a 70% faster turnaround from creative development to delivery. superside

Key AI Use Cases

• Custom image libraries — generating large volumes of unique, on-brand visuals (e.g., 3,300+ image components for a single project) superside
• Ad design at scale — rapidly producing and iterating on ad creatives acros

eonist

This is a fascinating and timely question. Here's a breakdown of the Fortune 500 companies and categories most vulnerable to decline if AI automates the bulk of white-collar work.

IT Services & Outsourcing Firms

These companies are arguably the most exposed, as their entire business model is built on selling human labor hours for knowledge work:

• Accenture – Already cut 11,000 jobs while pivoting to AI, but its revenue depends on deploying large teams of consultants and IT workers. When AI agents can replace a $3,000/month offshore developer at $500/month, the headcount-driven revenue model breaks down. linkedin
• Cognizant, Infosys, Wipro, TCS, HCLTech – Indian IT giants saw stock plunges of 4–8%+ in a single day after Anthropic announced enterprise AI automation features. Their core model—deploying large offshore teams for coding, testing, and back-offic

eonist

Yes, this feature is absolutely buildable — the spec, the API surface, and the existing Omni architecture all line up cleanly. Here's my assessment across both the feature itself and AFM compatibility.

Feature Feasibility

The core mechanism is straightforward: a single POST /repos/{owner}/{repo}/pulls/{pull_number}/reviews that atomically submits a summary, a verdict (APPROVE / REQUEST_CHANGES / COMMENT), and an array of inline comments each pinned to a path, line, and side . Omni already has the GitHub OAuth identity and write capabilities in githubWrite.ts, so the API plumbing is an extension of what exists .

The UX spec in the issue comments maps directly onto the existing PRView component tree — adding a ReviewList in the sidebar, a ReviewDetailView in the DetailsPanel, and inline annotations on the DiffViewer . The changes needed are well-scoped:

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Why We Think Automagic Actions + Human in the Loop is the Future of Git

While vibe code can automatically commit and make PRs, it has its fair share of downsides:

1. Excessive commits on every little thing. 100 commits when a human would need only 10. Especially when instructed to correct things after the fact.
2. Diff-based commit descriptions missing important holistic project knowledge.
3. AIs have limited context windows to deep dive into the intent of the code that was changed.

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Here's a comprehensive implementation plan for issue #240, based on the existing codebase .

What Exists Today

The PR view already has solid foundations to build on :

Component	Status	Location
File diff viewer	✅ Working	FileDetailView.tsx → DiffViewer
PR details view	✅ Working	PrDetailsView.tsx

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Here's a comprehensive implementation plan for AI Rebase, drawing from issue #177 , the existing split architecture in issue #196 , and the codebase structure .

High-Level Architecture

The AI Rebase is the inverse of the split feature — instead of one commit → many, it's many commits → fewer logical ones. You can mirror the existing split pipeline but reverse the data flow. The key files to model after are omni_commit.rs on the Rust side and the commit view components in src/views/commit/ .

Phase 1: Data Collection (Rust Backend)

Add a new Tauri command in src-tauri/src/ (e.g., omni_rebase.rs) that:

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Alright André, let's put Ashera AI through the gauntlet of your own Substack playbook. This is going to sting. 🔥

The Tagline: "GTM, Run by AI"

Your article says to "craft a crystal-clear value proposition that hooks in 5 seconds" and lead with a "crisp tagline". Ashera's tagline is "GTM, Run by AI". That's three letters (GTM), a comma, and a buzzword. It tells me absolutely nothing about what this product actually does. Is it a CRM? A dialer? A sales coach? A pipeline forecaster? A person skimming Product Hunt has already scrolled past before their brain finishes parsing the acronym. This is textbook "vague product positioning" — the #1 item on your own "Will Not Get You Featured" list. reddit

Me-Too Clone Alert 🚨

Your article explicitly warns: "Search Product Hunt for similar products first. If 10+ clones already exist, you're too late". AI-powered sales call analysis? Let's see… Go

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AI Rebase

We can also do the reverse. With code agents often having a tendency to create an excessive amount of commits, where humans used to make 10 commits, vibe code agents now often produce 100 or more. This can be solved with our AI Rebase feature.

Select the commits you want to auto rebase, right press with the mouse, and press Auto Rebase. As with the Auto Split feature, we run a recursive algorithm then use AI to decide what logical groups fit best together. Then we reuse the essential commit descriptions and carry them over if relevant. We also use our commit enricher algorithm to further improve descriptions in regards to what each commit now contains. Turn 100 commits into 14 commits that reads more cleanly. The Auto Rebase feature also reduces the amount of file change occurrence significantly.

AI Rebase: Decluttering the Commit Frenzy On the flip side of splitting, there's squashing. The AI Rebase feature lets you select a range of messy commits, and Omni's AI groups them into streamli