Your coding agent says "it's fixed." But is it, really? When AI agents fail, the problem usually isn't the model — it's the harness. In EP2 of #AgenticTalks#, Qoder reveals the 5-point fix. Aug 13, live on Alibaba Cloud. Register → #AlibabaCloud# #AICoding# #Qoder#

Your daily coffee costs more than your new AI copilot. ☕ FennoAI Trial: $1.99 for 7 days of completions, refactors & agent runs. Less than a latte. Probably more useful than one. Start shipping → #AIcoding# #devtools# #buildinpublic#

Numbers, because devs read numbers: 📉 • Trial — $1.99 / 7d (was $50) • Mini — $19.99 / mo (was $200) • Solo — $47.99 / mo (was $500) ← the daily driver • Multiplier: 1x (we don't tax your tokens) • Daily quota: unlimited Built for code: autocomplete · refactor · explain · PR review · agents. OpenAI cut prices. We cut the fat. #buildinpublic# #indiehackers# #devtools# #AIcoding# #shipit#

OpenAI just cut prices. Cool. We cut harder — on the one thing you actually burn tokens on all day: writing code. 🧠 → Autocomplete, explain, refactor, first‑pass PR review, agent loops → 1x multiplier = zero markup on your tokens → Unlimited daily quota Trial $1.99 / 7d · Daily driver $47.99 / mo Stop overpaying for your editor's brain. #buildinpublic# #devtools# #AIcoding#

The future of coding is AGENTIC. Thanks to all who joined our Qoder webinar! See how Qoder, our end-to-end AI coding agent, transforms dev workflows & boosts productivity. Try Qoder on us to streamline your dev lifecycle! 🔗 #Qoder# #AICoding# #AlibabaCloudPH#

🤖 AI writes code faster, but are we producing vulnerabilities faster? With AI generating over 40% of new code, traditional post-scanning just can't keep up. That’s why we built Qoder Security—shifting security left directly into the coding session. The Impact: • +60% vulnerability detection rate • -80% false-positive alerts • Hours to fix, not weeks From real-time regex interception to cross-file deep review, we’re embedding security natively into your workflow. 🚀Security starts with the first line of code. Try it out in Qoder Desktop & CLI today! Qoder Desktop (IDE) guide:  Qoder CLI guide:  #Qoder# #AICoding# #QoderSecurity# #CyberSecurity# #AgenticCoding#

# Cursor Features and Practical Usage 🧩 Tired of re-explaining the same multi-step workflow to your agent every single time? Cursor Skills let you package repeatable workflows so the agent just knows how to do them. 🏷️ Title: Reusable Workflows (SKILL.md) 🔗 URL: 📘 Overview Skills are portable, version-controlled packages that teach agents how to perform domain-specific tasks. They bundle scripts, templates, and reference material that the agent runs through its available tools. They are the evolution of Rules: agents can apply them automatically based on context, or you can invoke them explicitly as slash commands. ⚙️ How It Works Each skill is centered on a `SKILL.md` file whose leading YAML frontmatter defines its behavior. ・`name`: a lowercase identifier that must match the parent folder name (required) ・`description`: what the skill is for and when it applies; the agent reads this to decide whether to use it (required) ・`paths`: glob patterns that scope the skill to matching files (optional) ・`disable-model-invocation`: set to `true` to make it slash-only, included only when you type `/skill-name` (optional) Discovery is hierarchical: project skills live in `.cursor/skills/` (or `.agents/skills/`), and global ones in `~/.cursor/skills/`. The root is walked recursively, so nested subdirectories are found too. A skill folder can also ship `scripts/` (executable code), `references/` (docs loaded on demand), and `assets/` (templates or images). 🛠️ Practical Usage For example, in `.cursor/skills/api-endpoint/SKILL.md` set the frontmatter `name` to `api-endpoint`, a `description` of the workflow, and `paths` scoped to `src/api/**/*.ts`, then write the steps in the body (register the route, validate input with a zod schema, always add tests). If you do not want automatic invocation, add `disable-model-invocation: true` and call it explicitly by typing `/api-endpoint` in Agent chat. 💡 Use Cases In a monorepo, placing a `.cursor/skills/` folder inside each app automatically scopes those skills to files in that directory, so you can skip `paths` entirely. Share release procedures, migration scripts, or code-review checklists so the whole team works the same way. You can convert existing assets with the built-in `/migrate-to-skills` (Cursor 2.4): "Apply Intelligently" rules (`alwaysApply: false`) become skills, and slash commands become skills with `disable-model-invocation: true`. ⚠️ Caveats A skill's identity comes from the folder containing `SKILL.md`, not any parent category. The old `globs` field is deprecated; use `paths` now. `/migrate-to-skills` does not migrate `alwaysApply: true` rules or user-level rules, so those need manual handling. #Cursor# #AICoding#

# Antigravity Features and Practical Usage 🚀 "Think before doing" with Plan, "just do it" with Fast. Match caution and speed to the nature of each task. 📌 Title and Feature URL Title: Plan / Fast モード URL: 📝 Overview Antigravity has two execution modes. Plan mode generates a detailed plan (a Plan Artifact, the Implementation Plan) before acting and implements only after approval. Fast mode skips the planning phase, interpreting your request and executing immediately. The basic split is Plan for complex tasks, Fast for minor fixes. 🔧 How It Works The two modes behave as follows: - Plan mode: it analyzes scope and examines files, then generates an Implementation Plan covering the goal, technology choices, steps, file modifications, and testing approach. It implements after approval and records changes in a Walkthrough. - Interactive approval: highlight a section of the plan and comment; the agent incorporates it before implementation begins. - Fast mode: on a "just do it" philosophy, it executes immediately without plans or waiting for approval, then reports results. - Switching modes: use the interface controls or the keyboard shortcut (Cmd/Ctrl + .); the current mode shows in the input box. 🛠 Practical Usage - For complex refactors or production-affecting changes, approve the plan in Plan mode before starting. - For minor work like typo fixes, variable renames, or boilerplate, execute immediately in Fast mode. - Combine them: do foundational work in Plan, then switch to Fast for refinements. - Mode switches apply only to new requests; ongoing tasks continue in their original mode. 🎯 Use Cases - Approve a large refactor as a plan Artifact in Plan mode, then implement safely. - Knock out adding a button or fixing a typo instantly in Fast mode. - Confirm the approach in Plan for unfamiliar tech, then move to Fast once patterns are set. - Keep oversight via Plan for changes to production or critical systems. ⚠️ Caveats - Fast has no planning phase to resolve ambiguity, so be specific and keep to a single task rather than bundling many. - Fast trades thoroughness for speed and is not suited to critical changes. - Mode switches are not retroactive; switching takes effect from the next request. #Antigravity# #AIcoding#

# Cursor Features and Practical Usage 📏 "Always validate APIs with zod" — you shouldn't have to retype that policy every prompt. Cursor's Rules give the AI persistent memory. 🏷️ Title: Persistent Instructions (Project/Team/AGENTS.md) 🔗 URL: 📘 Overview Rules provide persistent, system-level instructions to Cursor's Agent. Since LLMs don't retain memory between completions, Rules supply reusable context at the prompt level. They bundle prompts, scripts, and guidance so workflows stay reusable across a team. ⚙️ How It Works Cursor supports several kinds of Rules. ・Project Rules: `.mdc` files under `.cursor/rules`, version-controlled and scoped to your codebase. ・User Rules: global preferences defined in Cursor Settings, applied across all projects. ・Team Rules: org-wide rules managed from the dashboard (Team/Enterprise plans). ・AGENTS.md: a plain-markdown alternative in the project root or subdirectories, no frontmatter needed and nestable (more specific instructions take precedence over parent ones). Project Rule frontmatter controls behavior: `alwaysApply: true` applies to every chat, `globs` with `alwaysApply: false` auto-attaches when matching files are in context, `description` only lets the Agent apply it when relevant, and with none of these it applies only via `@`-mention. 🛠️ Practical Usage ・Scope rules to file types with globs, e.g. `src/**/*.tsx`, comma-separating multiple patterns. This auto-applies "always validate APIs with zod" whenever matching files are edited. ・Generate rules in chat with `/create-rule`, or via `Cursor Settings > Rules, Commands` → "+ Add Rule." ・Example `.mdc`: a frontmatter with `globs: src/api/**/*.ts` and `alwaysApply: false`, followed by rules like "validate every incoming payload with a zod schema" and "on failure, return 400 with a unified error shape." ・For teams, remember the application order Team Rules → Project Rules → User Rules, and enforce company-wide conventions via Team Rules. 💡 Use Cases Turn repeated policies — "validate APIs with zod," "use Conventional Commits," "structured JSON logging" — into Rules, auto-applied only to matching files via globs. Check them into Git so the whole team benefits from the same conventions. ⚠️ Caveats Keep each rule under 500 lines and split larger ones. Avoid copying style guides (use linters), and prefer referencing files over duplicating content. Target frequent patterns, not rare edge cases. Note that User Rules apply only to Agent (Chat) — not to Inline Edit, other AI features, or Cursor Tab. #Cursor# #AICoding#

# Cursor Features and Practical Usage ✏️ No chat needed — select code and say "make this async" right where it lives. Cursor's Inline Edit is the shortest path to local fixes. 🏷️ Title: Cmd/Ctrl+K 🔗 URL: 📘 Overview Inline Edit lets you make focused code changes directly in the editor without opening the chat. Select code and press `Cmd+K` (Mac) / `Ctrl+K` (Windows/Linux), and an instruction box opens in place. It's built for fast, pinpoint edits. ⚙️ How It Works ・Give a natural-language instruction on the selected code and press `Return` to apply, e.g. "Convert this to an async function." ・It supports iterative refinement — request follow-up edits and they apply sequentially. ・Question mode: press `Opt+Return` (Mac) / `Alt+Return` (Windows/Linux) to ask about the selected code instead of editing it. If you want to implement a suggestion, type "do it" and confirm. ・Escalate to Agent: for larger, multi-file changes, select code and press `Cmd+L` (Mac) / `Ctrl+L` (Windows/Linux) to open Agent with your selection as context. 🛠️ Practical Usage ・Select a function and `Cmd+K` → "make it async," "add type annotations," "turn this branch into an early return" — cycle through local rewrites fast. ・When behavior is unclear, switch to question mode with `Opt+Return`, ask "what does this regex match?", then type "do it" to move to a fix if needed. ・When a fix grows complex and spreads across files, hand the selection to Agent with `Cmd+L` and escalate to autonomous implementation. 💡 Use Cases Quickly fix a single function flagged in review with `Cmd+K`, verify shaky logic in question mode before changing it, and promote to Agent once impact widens — a staged workflow that fits the size of the change. ⚠️ Caveats Inline Edit is meant for local, focused edits. Rather than forcing broad changes through `Cmd+K`, hand off to Agent with `Cmd+L` early for safer, more reliable results. Also note that User Rules generally apply only to Agent (Chat), not to Inline Edit. #Cursor# #AICoding#