The Intelligent Runtime for
Autonomous Engineering.
The only editor that codes, tests, and debugs in the background.
The Interface is Standard.
The Runtime is Recursive.
Dropstone is deployed as a fully compatible fork of VS Code. You get the zero-learning-curve interface you expect, powered by a D3 Runtime that provides infinite context retention and adaptive learning from your natural language interactions.
Never Repeat Yourself.
Dropstone learns from your chats. Tell it your coding preferences once—like "always use arrow functions"—and it will remember them forever. No more redundant prompting.
Model Behavior
Continuously learns from interaction.
Performance
Instantly applies rules to new chats.
Dropstone utilizes a vector-based latent memory system to retain infinite context without token limits.
Infinite Context.
It remembers your entire codebase, documentation, and past conversations. Never lose context again.
Data Scope
Codebase, docs, and full history.
Retention
Zero data loss across sessions.
Project Visualization: See your codebase structure in real-time.
Context Window.
We are truly extending the context window where We had to rethink how the model manages memory. 128k isn't a hard limit of intelligence; it's a limit of efficiency. We went back to the papers to virtualize the window and fix the retrieval bottleneck.
Read our researchArchitecture
Virtualization beyond 128k tokens.
Outcome
Eliminated retrieval bottlenecks.
Memory Virtualization: Dynamic context management.
Solves Problems,
Doesn't Just Write Code.
Standard AI forgets context as projects get large. Dropstone breaks complex features into small tasks and solves them autonomously.
Deterministic Decoupling. The D3 Engine separates state from probabilistic generation, routing tasks to optimized Scout Swarms.
Context Virtualization
Standard AI forgets things when the conversation gets too long. Dropstone separates 'Active Memory' (what you're doing now) from 'Long-term Storage' (history), allowing it to work on massive tasks for 24+ hours without getting confused.
Flash-Gated Consensus
Dropstone replaces standard generation with a rigorous peer-review loop. Agents must pass a verification step where other agents review their code in real-time. If the logic fails the review, it is rejected before you ever see it.
Hyper-Parallelized Search
We treat compute as a liquid asset. The system instantiates 10,000 ephemeral "Scout" agents to explore divergent solution trees. This allows the runtime to test low-probability strategies (P < 0.05) that linear models discard.
Think Before You Commit.
Most AI guesses the next word. Horizon Mode explores thousands of potential solutions in the background, testing them for bugs and logic errors before showing you the perfect one.
Scout Swarm Deployment (L1)
The system deploys up to 10,000 isolated "Scout" agents utilizing optimized Small Language Models (SLMs). These agents explore "low-probability" solution vectors
(P < 0.05) at near-zero marginal cost.
Negative Knowledge Propagation
When a Scout hits a dead end, it broadcasts a "Failure Vector" to the shared workspace. The swarm utilizes this Negative Knowledge to globally prune invalid logic branches in real-time.
Context Promotion (L2)
Upon identifying a candidate solution with high confidence (P > 0.85), the state is Promoted. The D3 Engine injects the relevant context into a Frontier Model for high-fidelity refinement.
The resulting code is not a generation—it is the surviving winner of
10,000 parallel experiments conducted within the D3 search space.
Runtime Primitives
Core architectural components designed for high-throughput engineering environments where latency and reasoning depth coexist.
Inference Routing
Intelligently assigns tasks: uses fast models for simple code and deep reasoning models for complex architecture.
Distributed Knowledge
Instantly shares learned mistakes across the swarm so no agent repeats an error.
Dynamic Distillation
Rigid separation of memory manifolds (Episodic, Sequential, Associative, Procedural) to prevent drift.
Context Promotion
Only solutions that are 85%+ verified are saved to long-term memory.
Engineering is
Multiplayer.
Dropstone keeps your team in perfect sync. It tracks the history of every decision and code change, allowing you to review deep reasoning trails or share context snapshots with a single click.
Temporal Playback
Replay the context construction to see exactly how the AI reached its conclusion.
Role-Based Context
Granular permissions ensure junior devs only see approved architecture patterns.
obs_stream :: user_joined [id:882]
ctx_update :: snapshot_generated (14kb)
<< awaiting remote ack...
Anti-Hallucination
Engine.
The system doesn't guess. It runs thousands of simulations in the background. If an agent's output varies too much (entropy), it is flagged as a hallucination and pruned instantly, forcing the swarm to agree on the single correct solution.
*Visual representation of variance reduction over 12 inference steps. Note the sharp pruning of the divergent red trajectory at t=4.
Live_feed :: activeAssociative
Semantic Graphing.
Dropstone doesn't just read code; it builds a dictionary of your project's unique terms. It resolves ambiguous names and definitions automatically.
function derive_state(ctx: Context) {
// Mapping inputs to recursive manifold
const entropy = 0.991;
const threshold = 0.850;
if (entropy > threshold) {
// Ambiguity detected. Recursive expansion.
return recursive_manifold(ctx);
}
await ctx.crystallize({
id: '0x992',
vector: [0.2, -0.4, ...]
});
}
Heuristic match failed.
Converged on state-preserving geometry. Serializing to node 0x992.
Visualizing 768-dim vector collapse.
Instant
Hive Mind.
Transform isolated work into shared intelligence. Unlike standard tools, when Dropstone learns a mistake from one developer, it instantly updates the entire team's context so no one repeats that error again.
Trajectory Forking
Agents can branch from any peer's causal graph without re-computing the context window.
Vector Sync
Lossless context sharing via compressed serialized state vectors using Protocol Buffers.
FIG 3.0: P2P State Synchronization
Sandboxed
& Secure.
Autonomous agents require a Deterministic Envelope. We utilize a multi-stage consensus protocol (Cstack) that verifies code execution in ephemeral, network-isolated sandboxes with kernel-level syscall filtering.
Adversarial Oversight
ISOLATION: MICRO_VMAll unverified logic is detained in network-gapped microVMs. Agents must pass "Property-Based Testing" where adversarial nodes attempt to inject edge-case failures.
Hallucination Reduction
P < 1.4%We monitor Semantic Entropy (Perplexity Spikes). If the PPL variance exceeds the safe threshold, the branch is immediately pruned via the Flash Protocol.
Verification Topology v2.1
Visualizing the double-gate validation process. Artifacts are subjected to adversarial sandboxing before passing entropy thresholds.
The Post-Linear
Paradigm.
Traditional software engineering hits a Linearity Barrier. As a system grows larger, it becomes harder for humans to maintain, causing progress to stall.
Dropstone removes this barrier. By using Recursive Swarms to write the implementation details, velocity actually increases as the system gets more complex.
Velocity vs. Complexity
Comparing Human limits against Recursive AI
Turn English into
Architecture.
Describe your goal in plain English. Dropstone understands your entire codebase deeply enough to refactor legacy code, spot architectural issues, and implement new features without breaking existing logic.
Powerful, yet bounded. We prioritize Prompt-Guided Execution. The agent amplifies intent; it does not hallucinate features.
State of Autonomy
Non-deterministic output. System outperforms industry benchmarks by orders of magnitude, yet human oversight remains required for commit ratification.
$refactor auth_flow.ts--strict --dry-run
Stop optimizing for latency.
Optimize for solution space.
Dropstone shifts the paradigm from speed to depth. Deploy the engine that reasons through high-dimensional ambiguity.