Crypto Cuts Continue: Algorand Trims 25% Of Workforce

bitcoinistPublicado em 2026-03-20Última atualização em 2026-03-20

Resumo

The Algorand Foundation has laid off 25% of its staff, citing a challenging global macroeconomic environment and a sustained downturn in the crypto market as the primary reasons. Despite the significant staff reduction, the organization maintains an ambitious roadmap for the year, including major updates to its AlgoKit, the launch of a new wallet called Rocca, and ongoing work on post-quantum security. This move reflects a broader trend of workforce reductions within the crypto industry, reminiscent of cuts made by companies like Coinbase and Gemini during the 2022 bear market. With Bitcoin trading 44% below its all-time high, financial pressures on crypto-native organizations continue to mount, potentially signaling further industry-wide consolidation and cost-cutting measures.

Peter Brandt thinks the crypto market has not hit bottom yet. If he is right, the Algorand Foundation’s decision to cut 25% of its staff may be just one of many similar moves still to come across the industry.

A Leaner Team, A Packed Roadmap

The Algorand Foundation announced the layoffs Wednesday, pointing to a rough stretch in global markets and a sustained pullback in crypto prices as the driving forces behind the decision.

The foundation described the move as painful but necessary, saying it had reached a more sustainable alignment between its spending and its long-term goals.

Affected workers were described as top contributors, and the organization said it would help them through the transition.

What makes the timing unusual is what the Foundation has on its plate for the year ahead. Reports indicate the organization is still pushing forward with several major projects — including the next big update to its developer toolkit AlgoKit, the launch of a new wallet called Rocca, and continued work on post-quantum security.

Cutting a quarter of your team while announcing an ambitious workload is a balancing act, and it remains to be seen whether the remaining staff can carry the load.

Bitcoin Down 44%, And Counting

The layoffs did not happen in a vacuum. Bitcoin is currently trading around $70,000 — roughly 45% below its all-time high of $126,000, which it hit in October.

At its lowest point earlier this year, it fell to $60,000. For foundations that hold portions of their treasury in crypto, a drop like that translates directly into less money to pay staff and fund operations.

Algorand has not been sitting still. Based on a December roadmap update, the Foundation reported it had doubled the amount of ALGO staked online — from around 1 billion to 2 billion — over the span of a little more than a year.

ALGOUSD now trading at $0.08. Chart: TradingView

That kind of growth signals momentum on the technical side, even as the financial pressures mount.

This Is Not The First Time The Crypto Industry Has Done This

The crypto world has been through rounds of staff cuts before. During the 2022 downturn, Coinbase reduced headcount by 18%, and Gemini cut 10% of its workforce.
Both moves came as Bitcoin was trading near two-year lows around $21,000.

This week, blockchain data company Messari also announced layoffs and the departure of its CEO, who stepped down as the company shifted its focus toward artificial intelligence.

Bullish CEO Tom Farley recently said the sector could see more consolidation ahead, with larger firms absorbing smaller ones and trimming overlapping roles in the process.

For the Algorand Foundation, the message is straightforward: do more with less, and stay the course.

Featured image from Unsplash, chart from TradingView

Perguntas relacionadas

QWhat percentage of its workforce did the Algorand Foundation cut?

AThe Algorand Foundation cut 25% of its workforce.

QWhat were the main reasons cited by the Algorand Foundation for the layoffs?

AThe layoffs were due to a rough stretch in global markets and a sustained pullback in crypto prices.

QWhat major projects does the Algorand Foundation still plan to push forward with despite the layoffs?

AThe Foundation is continuing work on the next update to AlgoKit, the launch of a new wallet called Rocca, and post-quantum security.

QHow much has Bitcoin fallen from its all-time high mentioned in the article?

ABitcoin is trading around $70,000, which is roughly 45% below its all-time high of $126,000.

QWhich other major crypto companies conducted layoffs during the 2022 downturn, as mentioned in the article?

ADuring the 2022 downturn, Coinbase reduced headcount by 18% and Gemini cut 10% of its workforce.

Leituras Relacionadas

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

"Old Dogs" Become AI's New Darlings: Revaluing Legacy Infrastructure The AI investment narrative is shifting. Beyond the spotlight on core chipmakers like Nvidia, a new wave of interest is rising for legacy tech companies—Dell, HPE, Nokia, Cisco, Corning, Western Digital—once labeled as slow-growth, outdated stories. This resurgence stems from AI's evolution from model development to real-world deployment, creating massive demand for physical infrastructure. As AI moves into data center construction and enterprise adoption, the focus turns to who can actually build and deliver complex systems. These established players hold decades of experience in supply chains, integration, networking, and enterprise delivery—assets now critical for scaling AI. The revaluation can be grouped into three key infrastructure areas: 1. **Servers & Integration (e.g., Dell, HPE):** They are becoming essential system integrators, transforming GPUs into full-scale AI servers with networking, power, and cooling, then delivering them to clients. Strong recent earnings and AI-specific revenue/order growth for Dell and HPE underscore this shift. 2. **Networking & Connectivity (e.g., Corning, Nokia, Cisco):** As AI clusters grow, high-speed data transfer becomes paramount. Corning benefits from fiber demand for data center links, Nokia is exploring AI-integrated wireless networks (AI-RAN), and Cisco sees surging orders for data center switches—all critical for efficient AI operations. 3. **Storage (e.g., Western Digital, Seagate):** The AI data explosion requires vast capacity. Beyond high-speed memory (HBM), there's growing need for high-capacity HDDs to store training data, logs, video, and cold/archival data cost-effectively. This revaluation, however, is not a blanket endorsement. True reassessment requires concrete proof: AI-driven orders and revenue growth, upward revisions to company guidance, and sustainable improvements in profit quality, not just top-line sales. In essence, AI is not turning all old tech firms into high-growth stocks; it is selectively re-pricing the "old assets" of companies that are mission-critical for building the new AI infrastructure, transforming their legacy capabilities into renewed growth engines.

marsbitHá 11m

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

marsbitHá 11m

Probability in the Price: How World Cup Odds Are Calculated

**The Probability in the Price: How World Cup Odds Are Calculated** Two major systems released their "championship probabilities" before the 2026 World Cup, and they disagreed on the favorite. Prediction market aggregators listed France at around **17%**, while the Opta supercomputer gave European champion Spain **16.1%**. These numbers look similar, but their production methods are fundamentally different. The market's **17%** is the **price** that clears after hundreds of millions of dollars in trading across platforms like Polymarket and Kalshi, where contracts trade between 0 and 100 cents, directly representing implied probability. This liquidity is provided by crypto-native market makers like Wintermute, though the market still has "the liquidity profile of an early-stage" asset class. In contrast, Opta's **16.1%** is a **simulated frequency**. Its model uses team data (including betting market odds as an input) to estimate match probabilities, then runs **10,000 full tournament simulations**, counting how often each team wins. Which is more accurate? There is **no rigorous, cross-tournament academic study** directly comparing their track records. However, a persistent **longshot bias**—where low-probability outcomes are systematically overvalued—observed in traditional betting for nearly a century, has also been found in modern crypto prediction markets. Research shows low-price contracts on Kalshi/Polymer less likely to pay out than their implied odds suggest. Unlike traditional bookmakers, prediction markets operate on **public blockchain ledgers**, making every transaction auditable and enabling such research. However, price formation is also influenced by **regulatory uncertainty**, as seen in recent US state-level bans and legal battles over jurisdiction. In summary, the "probability" you see is either a **market-clearing price** subject to behavioral biases and liquidity constraints, or a **model-simulated frequency** that partially incorporates market data. The question of which method is more reliable remains open, highlighting the importance of asking: **How was this number produced?**

marsbitHá 40m

Probability in the Price: How World Cup Odds Are Calculated

marsbitHá 40m

Trading

Spot
Futuros
活动图片