US Air Force picks Longshot to test hypersonic tech with ground-based launcher ⁠26%

By Sujita Sinha⁠28%

7/9/2026, 12:38:25 PM

BS Summary: This article contains 17 faulty reasoning types, including Optimism Bias, Self-Serving Bias, and Overconfidence Bias, with Attempt to Sell a Product or Service as the most egregious example at 26.8% saturation with 130 hits. Analysis detected 829 faulty-reasoning hits from 485 analyzed words, generating a BS Score of 38% and a BS Rank of ⁠26% (15,704 of 21,202 articles). This article is better (less manipulative) than 74.10% of the article peer group.

Longshot announced on July 8, 2026, that it has joined the U.S. 
Air Force’s new AEDC Velocity Alliance. 
This gives the kinetic space launch startup a chance to help modernize America’s hypersonic testing infrastructure. 
The Arnold Engineering Development Complex (AEDC) and the Air Force Test Center created the consortium to boost the nation’s testing abilities for next-generation defense technologies. 
The selection comes as Longshot continues expanding its hypersonic testing program following fresh funding and the acquisition of a larger California facility. 
The company says its accelerator technology could provide a more affordable way to test full-scale systems traveling at hypersonic speeds. 
Alliance targets next-generation defense testing 
The AEDC Velocity Alliance was established to create a pre-qualified network of industry partners capable of supporting engineering and construction projects across the Air Force’s testing infrastructure. 
Its focus is on upgrading and restoring facilities for evaluating advanced defense systems, including hypersonic technologies that operate at extremely high speeds and altitudes. 
Longshot is the only member of the alliance developing kinetic test accelerators to evaluate full-scale systems in low-level free flight. 
The company says its ground-based, multi-injection accelerator can propel payloads to hypersonic speeds without relying on conventional rocket launches. 
Unlike single-use missile tests that provide limited opportunities to collect data, the firm’s launcher is designed for repeated use. 
This allows engineers to conduct multiple test campaigns while reducing costs compared with traditional rocket-based testing. 
California facility to support larger launch systems 
The alliance announcement follows a recent $5 million investment, bringing Longshot’s total funding to $20 million. 
The company also secured a former U.S. 
Navy hangar at Alameda Point, California, as its new headquarters. 
The site will serve as the primary location for designing, assembling, and testing some of the world’s largest ground-based launch systems. 
Longshot plans to begin initial hydrogen testing in the fall of 2026. 
The company aims to accelerate payloads weighing up to 4.4 pounds (2 kilograms) beyond Mach 5, or more than 3,800 mph (6,100 km/h). 
A larger launcher is expected to follow in early 2027. 
That system is being designed to accelerate payloads weighing hundreds of tons to speeds between Mach 5 and Mach 7. 
Lower-cost approach to hypersonic research 
“We’re grateful for the support the Air Force is providing industry partners as we work to modernize testing at speed,” said Mark Bigham, Longshot’s Vice President of Defense. 
“Longshot gives the Velocity Alliance something unique: a way to generate hypersonic test conditions for full-scale systems on demand, at significantly lower cost and lead time than other approaches.” 
AEDC has already set aside federal funding for upcoming modernization projects covering test facilities and ranges across the United States. 
As a member of the Velocity Alliance, Longshot will be eligible to compete for future contracts tied to those infrastructure upgrades, potentially expanding the role of reusable ground-based hypersonic testing in U.S. defense research. 
Article reasoning-pattern comparisonThis article: 0.0%Sujita Sinha: 2.5%Interesting Engineering: 3.8%Confirmation Bias0.0%This article: 0.0%Sujita Sinha: 0.4%Interesting Engineering: 1.2%Anchoring Bias0.0%This article: 0.0%Sujita Sinha: 2.2%Interesting Engineering: 2.5%Availability Heuristic0.0%This article: 4.1%Sujita Sinha: 0.6%Interesting Engineering: 1.2%Representativeness Heuristic4.1%This article: 0.0%Sujita Sinha: 0.2%Interesting Engineering: 0.3%Hindsight Bias0.0%This article: 14.0%Sujita Sinha: 5.2%Interesting Engineering: 5.2%Overconfidence Bias14.0%This article: 2.1%Sujita Sinha: 3.3%Interesting Engineering: 6.4%Framing Effect2.1%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.2%Loss Aversion0.0%This article: 7.0%Sujita Sinha: 0.9%Interesting Engineering: 0.6%Status Quo Bias7.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.5%Sunk Cost Effect0.0%This article: 24.5%Sujita Sinha: 11.3%Interesting Engineering: 17.1%Optimism Bias24.5%This article: 0.0%Sujita Sinha: 0.6%Interesting Engineering: 0.5%Pessimism Bias0.0%This article: 3.9%Sujita Sinha: 2.4%Interesting Engineering: 0.9%Negativity Bias3.9%This article: 19.8%Sujita Sinha: 4.9%Interesting Engineering: 4.5%Self-Serving Bias19.8%This article: 0.0%Sujita Sinha: 0.5%Interesting Engineering: 0.1%Fundamental Attribution Error0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Actor-Observer Bias0.0%This article: 0.0%Sujita Sinha: 0.5%Interesting Engineering: 0.9%In-Group Bias0.0%This article: 0.0%Sujita Sinha: 0.3%Interesting Engineering: 0.1%Out-Group Homogeneity Bias0.0%This article: 11.8%Sujita Sinha: 2.5%Interesting Engineering: 5.1%Halo Effect11.8%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Horn Effect0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Dunning-Kruger Effect0.0%This article: 5.4%Sujita Sinha: 1.7%Interesting Engineering: 1.0%Recency Bias5.4%This article: 0.0%Sujita Sinha: 0.2%Interesting Engineering: 0.2%Primacy Effect0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Blind-Spot Bias0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Ad Hominem0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Straw Man0.0%This article: 6.0%Sujita Sinha: 4.4%Interesting Engineering: 8.8%Appeal to Authority6.0%This article: 3.9%Sujita Sinha: 1.3%Interesting Engineering: 1.5%False Dilemma3.9%This article: 0.0%Sujita Sinha: 0.8%Interesting Engineering: 0.3%Slippery Slope0.0%This article: 0.0%Sujita Sinha: 0.1%Interesting Engineering: 0.1%Circular Reasoning0.0%This article: 6.0%Sujita Sinha: 2.6%Interesting Engineering: 5.0%Hasty Generalization6.0%This article: 0.0%Sujita Sinha: 0.1%Interesting Engineering: 0.1%Red Herring0.0%This article: 0.0%Sujita Sinha: 0.2%Interesting Engineering: 0.8%Bandwagon0.0%This article: 0.0%Sujita Sinha: 5.2%Interesting Engineering: 2.3%Appeal to Emotion0.0%This article: 0.0%Sujita Sinha: 1.2%Interesting Engineering: 1.2%Begging the Question0.0%This article: 11.1%Sujita Sinha: 2.6%Interesting Engineering: 2.1%Post Hoc (False Cause)11.1%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Tu Quoque0.0%This article: 7.0%Sujita Sinha: 1.0%Interesting Engineering: 0.6%Burden of Proof7.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.2%Appeal to Nature0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.3%Composition/Division0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.7%Anecdotal0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.1%No True Scotsman0.0%This article: 0.0%Sujita Sinha: 1.1%Interesting Engineering: 2.6%Ambiguity (Equivocation)0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Middle Ground0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Personal Incredulity0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.1%Special Pleading0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Genetic Fallacy0.0%This article: 5.8%Sujita Sinha: 1.5%Interesting Engineering: 1.8%Unattributed Quote5.8%This article: 0.0%Sujita Sinha: 1.5%Interesting Engineering: 0.7%Quote-first Misdirection0.0%This article: 11.8%Sujita Sinha: 1.0%Interesting Engineering: 3.9%Biased Writer Voice11.8%This article: 0.0%Sujita Sinha: 1.2%Interesting Engineering: 0.7%Indoctrination0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Sujita Sinha: 0.0%Interesting Engineering: 0.1%Politically Right Leaning Bias0.0%This article: 26.8%Sujita Sinha: 4.1%Interesting Engineering: 10.6%Attempt to Sell a Product or S…26.8%

485 words analyzed.

Speakers

3speakers35%attributed speech315writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 0.0% coverageLongshot • 12 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageLongshot • 20 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 20 words • 100.0% coverageLongshot • 19 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageLongshot • 7 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 21 words • 100.0% coverageLongshot • 12 words • 0.0% coverageLongshot • 23 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 5 words • 100.0% coverageMark Bigham • 28 words • 100.0% coverageMark Bigham • 29 words • 100.0% coverageAEDC • 20 words • 0.0% coverageWriter's voice • 34 words • 100.0% coverage
Selected voice

Mark Bigham

100%flagged-word coverage
57 attributed words34% of attributed speech65% writer coverage
0%27.5%55.0%Attempt to Sell a Product +38.5 ptsWriter: 12.4%Mark Bigham: 50.9%50.9%Unattributed Quote+49.1 ptsWriter: 0.0%Mark Bigham: 49.1%49.1%Biased Writer Voice-18.1 ptsWriter: 18.1%Mark Bigham: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.